Senior Data Architect

About the Role – Senior Data Architect

Responsibilities

• Design and Strategy : Work with data architecture team to define data architecture blueprints for our products, including data flow diagrams, system integrations, and storage solutions. Continuously refine the architecture to meet evolving business requirements and to incorporate new AWS capabilities and industry best practices. Drive adoption of and oversee adherence to architecture and standards.
• Cloud Data Platform Development : Lead the development of our cloud-based data platform on AWS. Implement data pipelines and warehouses using AWS services – e.g., AWS Glue for ETL, AWS Lambda for serverless processing, Amazon Redshift for data warehousing, and S3 for data storage. Ensure that data is efficiently extracted, transformed, and loaded to support AI, automation, and analytics & reporting needs.
• Big Data & Legacy Integration : Oversee the ingestion of large-scale datasets from various sources (transactional systems, APIs, external files). Optimize processing of big data using Spark and integrate legacy Hadoop-based data into our AWS environment.
• Data Modeling: Develop and maintain data models (conceptual, logical, physical) for our databases and data lakes. Design relational schemas and dimensional models that cater to both operational applications and analytical workloads. Ensure data is organized for easy access and high performance (for example, optimizing Redshift schema design and using partitioning or sort keys appropriately).
• Advanced Analytics Enablement : Work closely with Data Science and Analytics teams to enable AI and advanced analytics. Provide well-structured data sets and create pipelines that feed machine learning models (e.g., customer personalization models, predictive analytics). Implement mechanisms to handle real-time streaming data (using tools like Kinesis or Kafka if needed) and ensure data quality and freshness for AI use cases.
• Efficiency and Scalability : Design efficient, scalable processes for data handling. This includes optimizing ETL jobs (monitoring and tuning Glue/Spark jobs), implementing incremental data loading strategies instead of full loads where possible, and ensuring our data infrastructure can scale to growing data volumes. You will continually seek opportunities to automate manual data management tasks and improve pipeline reliability (CI/CD for data pipelines).
• Data Governance & Security : Embed data governance into the architecture – implement data cataloging, lineage tracking, and governance policies. Ensure compliance with data privacy and security standards: implement access controls, encryption (at-rest and in-transit), and data retention policies aligned with Alight and client requirements. Work with the InfoSec team to perform regular audits of data access and to support features like data masking or tokenization for sensitive information.
• Collaboration and Leadership : Collaborate with other technology leadership and architects, product managers, business analysts, and engineering leads to understand data needs and translate them into technical solutions. Provide technical leadership to data engineers – set development standards, guide them in choosing the right tools/approaches, and conduct design/code reviews. Lead architecture review sessions and be the go-to expert for any questions on data strategy and implementation.
• Innovation and Thought Leadership: Stay abreast of emerging trends in data architecture, big data, and AI. Evaluate and recommend new technologies or approaches (for example, evaluate the use of data lakehouses, graph databases, or new AWS analytics services). Provide thought leadership on how Alight can leverage data for competitive advantage, and pilot proof-of-concepts for new ideas.

Required Qualifications

• Experience : 12+ years (preferred 15+ years) of experience in data architecture, data engineering, or related fields, with a track record of designing and implementing large-scale data solutions. Demonstrated experience leading data-centric projects from concept to production.
• Cloud & Big Data Expertise : Hands-on expertise with AWS data services – especially AWS Glue, Lambda, Redshift, and S3. Proficiency in designing data pipelines and warehousing solutions on AWS is a must. Strong experience with big data technologies including Hadoop and Spark; able to optimize heavy data processing jobs and troubleshoot performance issues in distributed data systems.
• Data Modeling & Warehousing : Exceptional skills in data modeling and database design. Able to design dimensional or normalized schemas. Deep understanding of SQL and proficiency in writing and tuning complex queries. Experience building and maintaining a enterprise data warehouse or data lake, including partitioning strategies, indexing, and query optimization.
• Programming & Scripting : Proficiency in programming for data engineering – Python (or Scala/Java) for ETL/ELT scripting, and solid SQL skills for data manipulation and analysis. Experience with infrastructure-as-code (Terraform/CloudFormation) and CI/CD pipelines for deploying data infrastructure is a plus.
• Analytics and AI Orientation : Knowledge of machine learning concepts and experience supporting data science teams. You should understand how to prepare data for modeling and have experience with one or more tools or frameworks for data analysis. Experience with real-time data streaming and processing (Kinesis, Kafka, or similar) is a plus, as is exposure to AI/ML services (like Amazon SageMaker or Bedrock).
• Leadership & Soft Skills : Excellent communication skills with an ability to explain complex architectures in simple terms. Experience collaborating in cross-functional teams and leading technical initiatives. Proven ability to mentor junior engineers and to establish best practices in code quality, documentation, and data pipeline design. A problem-solving mindset and the flexibility to work in a fast-paced, evolving environment.
• Education: Bachelor’s degree in Computer Science, Information Systems, or a related field required. (Master’s degree in a relevant field is a plus.)
• Certifications : (Preferred) AWS Certified Solutions Architect or AWS Certified Data Analytics certification. Any big data or database certifications (Cloudera Data Platform, Oracle/SQL Server certs, etc.) will be a plus and reinforce your expertise in the field.

Application and Interview

• By applying for a position with Alight, you understand that, should you be made an offer, it will be contingent on your undergoing and successfully completing a background check consistent with Alight’s employment policies. Background checks may include some or all the following based on the nature of the position: Government ID validation, education verification, employment verification, and criminal check, search against global sanctions and government watch lists, credit check, and/or drug test. You will be notified during the hiring process which checks are required by the position.
• Alight requires all virtual interviews to be conducted on video. Please be aware that Alight is a camera-on culture and may require occasional travel to one of our physical office locations.

Our commitment to Inclusion

Equal Opportunity Policy Statement

Authorization to work in the Employing Country