Lead Data Engineer - R01561308
Team: AI & Data Engineering : Data Engineering
Location: Chicago, Illinois, United States
Commitment: Employee
Workplace Type: onsite
Primary Skills
- Athena, Step Functions, Spark - Pyspark, ETL Fundamentals, SQL (Basic + Advanced), Glue, Python, Lambda, Data Warehousing, EBS /EFS, AWS EC2, Lake Formation, Aurora, S3, Modern Data Platform Fundamentals, PLSQL, Data Modelling Fundamentals, Cloud front
Job requirements
- About the Role
- We are seeking an experienced Data Engineer to design and build scalable, cloud-native data platforms supporting IoT, operational systems, and enterprise analytics.
- This role requires a hands-on technical leader who can architect modern data pipelines, enable real-time and batch ingestion, and design performant serving layers for APIs and applications.
- The ideal candidate blends deep AWS expertise, strong data modeling skills, and the ability to translate business requirements into scalable technical solutions.
- Data Engineering & Architecture
- Architect ingestion pipelines for streaming and event-based data (IoT telemetry)
- Implement time-window logic and event-to-state transformations
- Design, build, and optimize data pipelines using AWS Glue, Lambda, and Step Functions for ingestion, transformation, and curation.
- Develop and maintain data lakes (S3 + Lake Formation) and data warehouses (Redshift) to support analytics and visualization.
- Integrate Aurora (PostgreSQL/MySQL) as a serving layer for APIs and dashboards.
- Design APIs or direct query interfaces that expose curated datasets for React-based dashboards and web applications.
- Define and implement data models, partitioning strategies, and schema evolution best practices for performance and scalability.
- Implement data security policies, encryption, and role-based access controls using AWS IAM, KMS, Lake Formation, and Secrets Manager.
- Ensure compliance with organizational data governance and privacy standards.
- Maintain data cataloging, lineage, and access tracking within AWS Glue Data Catalog and Lake Formation.
- Implement CI/CD pipelines for data workflows in collaboration with DevOps teams.
- 12+ years of experience in data engineering and AWS data architecture.
- Strong expertise with AWS Glue, Redshift, S3, Lake Formation, Aurora (Postgres/MySQL).
- Proven experience building APIs or exposing curated datasets for web applications (preferably React or similar front-end frameworks).
- Strong programming skills in Python and SQL.
- Experience with data modeling, ETL/ELT frameworks, and performance optimization.
- Working knowledge of Terraform/CloudFormation and CI/CD practices.
- Understanding of data security, IAM policies, encryption, and governance frameworks.
- Experience with Athena for ad-hoc analytics.
- Familiarity with API Gateway, AppSync, or GraphQL APIs for serving data to front-end applications.
- Knowledge of event-driven pipelines (Kinesis, EventBridge, kafka) and data quality monitoring.
- Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation.
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