2,282 Data Architect jobs in the United States

PST candidates only

Must Haves

1. Strong project experience in Big Data, Cloudera Distribution 7.x, Cloud migration, RDBMS is must.
2. Strong project experience with Amazon EMR/Databricks/Cloudera CDP is must.
3. 4-5 experience building data pipelines using Hadoop components Sqoop, Hive, Solr, MR, Impala, Spark, Spark SQL., HBase.
4. 4-5 years of programming experience in Python, Java and Scala is must.
5. Strong experience with REST API development using Python frameworks (Django, Flask etc.)
6. Micro Services/Web service development experience using Spring framework is highly desirable

At EY, we're all in to shape your future with confidence.

We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

The opportunity

EY is a global leader in assurance, tax, transaction and advisory services. Technology is at the heart of what we do and deliver at EY. Technology solutions are integrated in the client services we deliver and are key to our innovation as an organization.

Fueled by strategic investment in technology and innovation, Client Technology seeks to drive growth opportunities and solve complex business problems for our clients through building a robust platform for business and powerful product engine that are vital to innovation at scale. As part of Client Technology, you'll work with technologists and business experts, blending EY's deep industry knowledge and innovative ideas with our platforms, capabilities, and technical expertise. As a catalyst for change and growth, you'll be at the forefront of integrating emerging technologies from AI to Data Analytics into every corner of what we do at EY. That means more growth for you, exciting learning opportunities, career choices, and the chance to make a real impact.

The selected candidate

• Needs to be hands-on with design and implementation of scalable data pipelines, ETL processes, and data warehousing solutions to align with Azure Well-Architected Framework (WAF) pillars

• Accountable for a suite of data models with relatively high complexity, leveraging a strong understanding of data modelling standards to ensure high quality

• Drive best practices for data security, data privacy, and data integrity

• Ensure the reliability and efficiency of data infrastructure in the Azure cloud

• Understands AI driven data engineering tools; and work on building cutting edge AI driven use cases and ensure availability of AI ready data

• Works with other departments across the business to help define and deliver business value, as well as interfacing and communicating with program teams, management and stakeholders to deliver large, complex projects

Your key responsibilities include

• Leading the production of high-quality data engineering deliverables, helping to ensure project timelines are met, and providing informal mentoring / training to junior members of the team

• Leading the design, development and implementation of processes to extract, transform and load data from disparate sources into a form that is consumable by analytics processes within a given project, reviewing deliverables to ensure high quality

• Develop and define future state data architectures aligned with industry best practices and organizational needs

• Proficient in designing Data Architecture strategy, developing data architecture for modern data platform, assessing enterprise existing data architecture and devise recommendations

• Leading translation of requirements, design and solution architecture deliverables into detailed design specifications

• Define and implement data management strategies to align with business objectives

• Leading the delivery of data quality reviews including data cleansing where required to ensure integrity and quality

• Evaluating and resolving issues regarding data quality reviews, cleansing, data integration and migration, leveraging advanced technical knowledge and showing technical leadership in aspects of data engineering while driving continuous improvement efforts

• Providing a leadership role for the work group, ensuring the appropriate expectations, principles, structures, tools and responsibilities are in place to deliver

• the project

• Analyzing the latest industry trends such as cloud computing and distributed processing and inferring potential impact on businesses (short and long-term)

• Providing advanced technical expertise to maximize efficiency, reliability and value from current data engineering processes. Researching and monitoring existing client base and industry developments to identify potential new product opportunities from emerging technologies

• Developing strong working relationships with peers across engineering, collaborating to develop leading data engineering solutions

• Driving adherence to the relevant data engineering and data modeling processes, procedures, standards, and may input into the definition, maintenance and implementation of technology standards

Skills and attributes for success

• Data Architecture: Able to design and implement data architecture solutions that meet organizational needs by leveraging the Azure Well-Architected Framework (WAF) pillars (Cost Optimization, Operational Excellence, Performance Efficiency, Reliability, and Security)

• Infrastructure Architecture Diagrams: Able to create and deliver Azure Infrastructure Architecture Diagrams (IAD) that visually represent the architecture of

• data solutions, ensuring clarity and alignment with best practices.

• Data Extraction - Capability to design an efficient way of extracting high volumes structured and unstructured data with an automation CDC capability.

• Data Ingestion - Capability to design efficient ingestion strategy for batch processing as well as stream processing of all verity of source data that produces on the transactional systems as fast as it is.

• Data Processing - Capability to design and implement models, capabilities and solutions to process data within the enterprise (data validation, data quality, data profiling, etc.).

• Data Modeling - Capability to designs, develops and produces data models of relatively high complexity, leveraging a sound understanding of data modelling standards to ensure high quality.

• Data Store - Capability to designs data storage models, storage requirements and migration of data from one system to another.

• Data Consumption - Capability to designs data consumption mechanism with APIs, Virtualization and Visualization tools.

• Data Governance - Capability to designs a governance mechanism including data catalogue, lineage, classification, MDM, exploration.

• Data Security: Able to design and implement various authentication and authorization methods to ensure Data security

• Data Integration: Develop and manage data integration strategies, including ETL processes, to ensure seamless data flow and accessibility across systems.

Required Technical Skills

• Handson experience in building Data Architecture using various data architecture patterns like Data Mesh, Data Fabric, Data Lakehouse, Data observability & Data as a Service (DaaS)

• Proficient in Azure services (e.g., Azure Data Lake, Azure SQL Database, Azure Synapse Analytics) to build scalable and efficient data solutions.

• Experience in building data orchestration through Azure Data Factory, Function App, Logic App.

• Proficient in SQL and familiar with programming languages such as Python and Java

• Extensively worked on Databricks performance optimization (includes data Ingestion, transformation and consumption areas)

• Experience designing and building Data Platforms integrating disparate data sources

• Experience in design and development of various authentication and authorization methods to ensure data security.

• Expertise in working with MPP designs to speeds the performance of huge databases that deal with massive amounts of data

• Expertise in Azure, Azure Data Bricks, Azure SQL, Spark

• Expertise developing dataflows using NiFi/ADF, Databricks

• Advanced, hands-on design and implementation experience of large analytic warehouse.

• Advanced, hands-on experience in Spark architecture and implementation using several methods

• Experience in working with Distributed Message Systems like Kafka.

• Hands on experience on Python, PySpark or R.

• Expert in creating and analyzing complex SQL queries and procedures.

• Understanding of big data and distributed Architecture.

• Creating Ingestion workflows using Oozie or similar tools

• Knowledge of security measures like HTTPS and Kerberos

Beneficial Technical Skills

• Azure Data Lake Store, Databricks Delta Lakes

• Experience using NoSQL databases

• Advanced Analytics, ML and AI

• Knowledge in Graph Databases, preferably Neo4J, Cypher and CosmosDB

• Experience developing Microservices

Education

• B.E. / M.S. Computer Science, Data Analytics, Data Science, Engineering, IT, or related field preferred

• Big Data Certification from either Cloudera/Hortonworks/Databricks

What we look for

• Strong analytical skills and problem-solving ability

• A self-starter, independent-thinker, curious and creative person with ambition and passion

• Excellent inter-personal, communication, collaboration, and presentation skills

• Customer focused

• Excellent time management skills

• Positive and constructive minded

• Takes responsibility for continuous self-learning

• Takes the lead and makes decisions in critical times and tough circumstances

• Attention to detail

• High levels of integrity and honesty

What we offer you

The compensation ranges below are provided in order to comply with United States pay transparency laws. Other geographies will follow their local salary guidelines, which may not be a direct conversion of published US salary ranges. At EY, we'll develop you with future-focused skills and equip you with world-class experiences. We'll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more .

• We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $145,500 to $80,000. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is 174,500 to 318,200. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

• Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.

• Under our flexible vacation policy, you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.

Are you ready to shape your future with confidence? Apply today.

EY accepts applications for this position on an on-going basis.

For those living in California, please click here for additional information.

EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law?

EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at .

What We Do/Project

As part of the transformation, we are establishing a modern, governed, and reusable data foundation to power financial forecasting, title economics, sales planning, and AI-driven insights.

The Senior Data Architect plays a critical role in designing this foundation-ensuring that data models, pipelines, and integration frameworks are scalable, performant, and aligned with enterprise data governance and platform goals.

Embedded within the Platform Pod, the Senior Data Architect partners with the Platform Owner, Cloud Architect, data engineering teams, and product-aligned pods to ensure the architecture supports both immediate product needs and long-term platform evolution. This role directly enables the delivery of reliable, real-time, and reusable data products across multiple workstreams.

Job Responsibilities / Typical Day in the Role
Design Scalable and Consistent Data Architecture
• Define and maintain canonical data models, entity relationships, and semantic layer specifications that ensure consistent use of data across products and domains.
• Develop and evolve logical and physical data models that support real-time analytics, forecasting, and scenario planning.
• Collaborate with product-aligned pods to design domain-aligned data products that are modular, governed, and discoverable.
Build Reusable, Performant Data Pipelines
• Architect data pipelines that support both batch and near real-time processing using AWS-native services (e.g., Glue, Kinesis, Lambda, Step Functions).
• Guide ingestion, transformation, and enrichment strategies that optimize for resilience, scalability, and lineage traceability.
• Work closely with the Cloud Architect to ensure that infrastructure and orchestration layers meet pipeline and data SLAs.
Embed Governance and Stewardship by Design
• Partner with enterprise data governance teams to implement standardized metadata, lineage, and access controls using tools such as Lake Formation, Informatica, or Snowflake.
• Define data quality rules, validation checkpoints, and anomaly detection processes to support trusted analytics and ML pipelines.
• Contribute to the enterprise data catalog and enable self-service access through secure, well-documented APIs and schemas.
Collaborate Across Platform and Product Pods
• Work with the Platform Owner to define and deliver shared data services and reusable semantic models that support multi-pod alignment.
• Support data scientists and analysts by enabling ML/AI-ready data pipelines and structuring data to accelerate model development and deployment.
• Participate in cross-pod architecture planning to coordinate integration strategies, resolve semantic conflicts, and align on domain boundaries.

Must Have Skills / Requirements
1) Experience in data architecture and engineering, with a focus on cloud-native data platforms and modern analytics workflows.
a. 7+ years of experience; Designing and delivering data architecture for cloud-based platforms, with strong knowledge of AWS (e.g., Glue, Lambda, Step Functions, Lake Formation) and modern tooling (e.g., Snowflake, Databricks, Informatica).
2) Hands-On Pipeline Design and Orchestration
a. 7+ years of experience; Experience architecting and optimizing complex data pipelines-ensuring performance, resilience, and real-time capabilities; Hands-on experience building batch and streaming pipelines that are performant, resilient, and traceable-using orchestration frameworks that support real-time and ML/AI-ready processing.
3) Expertise in Canonical Modeling and Semantic Design
a. 7+ years of experience; Proven ability to design scalable, reusable data models and translate them into physical implementations that align with business domains and analytic needs; Deep proficiency in designing canonical and semantic data models, with proven experience aligning data structures to business domains and analytic use cases.

Nice to Have Skills / Preferred Requirements
1) None

Functional Knowledge / Skills in the following areas:
1) You'll thrive in this role if you naturally:
a. Think in Domains and Products
b. You understand that good data architecture starts with clear business semantics, and you design models that reflect the real-world entities behind Studio workflows.
c. Bridge the Gap Between Models and Platforms
d. You work fluidly across logical design, physical deployment, and infrastructure orchestration-partnering with Cloud Architects and Engineers to bring your models to life.
e. Govern Through Enablement
f. You ensure compliance, lineage, and quality by embedding governance directly into design-making the right path the easy path for product and engineering teams.
g. Build for Reuse and Interoperability
h. You optimize for consistency and extensibility-designing assets and APIs that can be adopted across products, use cases, and future data science workflows.
i. Promote Transparency and Stewardship
j. You advocate for shared ownership of data definitions and practices and help business and technical stakeholders understand the value of consistency and quality.
2) You're likely a fit for this role if you bring:
a. Cross-Functional Collaboration
b. Strong ability to work across disciplines-including engineering, analytics, product, and compliance-and communicate design decisions in a way that drives alignment and adoption.
c. Bias for Structure and Clarity
d. You drive resolution of semantic conflicts, minimize redundancy, and create architectural clarity that simplifies downstream implementation.
e. Excellent collaboration and communication skills, with the ability to facilitate cross-functional alignment and translate architectural decisions across technical and business audiences.

Technology Requirements:
1) You're likely a fit for this role if you bring:
a. Deep Data Architecture Experience
b. Experience designing and delivering data architecture for cloud-based platforms, with strong knowledge of AWS (e.g., Glue, Lambda, Step Functions, Lake Formation) and modern tooling (e.g., Snowflake, Databricks, Informatica).
c. Expertise in Canonical Modeling and Semantic Design
d. Proven ability to design scalable, reusable data models and translate them into physical implementations that align with business domains and analytic needs.
e. Deep proficiency in designing canonical and semantic data models, with proven experience aligning data structures to business domains and analytic use cases.
f. Hands-On Pipeline Design and Orchestration
g. Experience architecting and optimizing complex data pipelines-ensuring performance, resilience, and real-time capabilities.
h. Hands-on experience building batch and streaming pipelines that are performant, resilient, and traceable-using orchestration frameworks that support real-time and ML/AI-ready processing.
i. Governance and Metadata Awareness
j. Familiarity with data governance practices, including stewardship, lineage, access controls, and cataloging across enterprise environments.
k. Familiarity with data governance frameworks, including data quality rules, lineage tracking, access controls, and enterprise metadata management.
2) Other Qualifications:
a. Ability to partner with platform and cloud engineering teams to ensure infrastructure and orchestration layers support data reliability, scalability, and SLAs.
b. Strong understanding of data product design principles and ability to develop modular, reusable data services that support multiple products and delivery pods.
c. Experience contributing to or maintaining an enterprise data catalog and enabling self-service access through secure, well-documented APIs.

Additional Notes
• Hybrid schedule (Tues-Thurs) required (Burbank, CA)

#LI-NN2
#LI-hybrid
#DICE

Must Have Technical/Functional Skills:

• Database design, data modeling, data warehousing, SQL, ETL processes, cloud technologies, data mining.

• Programming languages like Python and Java.

Roles & Responsibilities

• Designing and developing data models to fulfill the organization's strategic data needs.

• This includes conceptual, logical, and physical data models.

• Establishing the overall structure for how data is managed, including standards, policies, and procedures.

• Ensuring data is protected and adheres to relevant regulations and policies.

• Designing and implementing solutions for integrating data from various sources.

• Establishing and enforcing data quality, consistency, and accessibility standards.

H i

Hope you are doing good,

This is Sangeetha from Info Way Solutions; LLC We have job opening for

the below requirement , the detailed Job description is given below:

Data Architect
Location: Austin, TX ( Onsite )

Responsibilities:
Design and implement effective database solutions and models to store and retrieve company data.
Examine and identify database structural necessities by evaluating client operations, applications, and programming.
Assess database implementation procedures to ensure they comply with internal and external regulations.
Install and organize information systems to guarantee company functionality.
Prepare accurate database design and architecture reports for management and executive teams.
Oversee the migration of data from legacy systems to new solutions.
Monitor the system performance by performing regular tests, troubleshooting, and integrating new features.
Recommend solutions to improve new and existing database systems.
Educate staff members through training and individual support.
Offer support by responding to system problems in a timely manner.
Requirements:
Bachelor's degree in computer science, computer engineering, or relevant field.
A minimum of 5 years' experience in a similar role.
Strong knowledge of database structure systems and data mining.
Excellent organizational and analytical abilities.
Outstanding problem solver.
Good written and verbal communication skills.ck the JD and share your views

Thanks & Regards,

Sangeetha



Direct:

Work: Ext 104



Info Way Solutions LLC | 46520 Fremont Blvd, Suite 614 | Fremont, CA - 94538

Has worked in the past as an Architect.
Professional experience in Data Engineering using Google Big Query (GBQ) and Google Cloud Platform (GCP) data sets and building data pipelines.
Hands on and deep experience working with Google Data Products (e.g. BigQuery, Dataflow, Dataproc, Dataprep, Cloud Composer, Airflow, DAG etc.).
Python Programming Expert PySpark, Pandas
Experience in Airflow (Create DAG, Configure the variables in Airflow, Scheduling)
Big Data technologies and solutions (Spark, Hadoop, Hive, MapReduce) and multiple scripting and languages (YAML, Python).
Experience in DBT to create the lineage in GCP. - Optional
Worked in Dev-Sec-Ops (CICD) environment.
Design and develop the ETL ELT framework using BigQuery, Expertise in Big Query concepts like Nested Queries, Clustering, Partitioning, etc.
Experience in Data Integration, Data Transformation, Data Quality and Data Lineage tools.
Should be able to automate the data load from Big Query using APIs or scripting language.
E2E Data Engineering and Lifecycle (including non-functional requirements and operations) management.
E2E Solution Design skills - Prototyping, Usability testing and data visualization literacy.
Experience with SQL and NoSQL modern data stores.