Data Engineering Architect | Hybrid Boston,MA
Roles & Responsibilities
15+ years of overall experience in data engineering, data architecture, data warehousing, or business intelligence.
Strong hands-on experience with AWS cloud data services and enterprise-scale Databricks platforms.
Advanced experience with Python, PySpark, Apache Spark, SQL, and Delta Lake.
Proven experience designing and implementing enterprise data pipelines and metadata-driven frameworks.
Strong expertise in ETL/ELT architecture, orchestration, optimization, and production operations.
Extensive knowledge of Lakehouse and Medallion Architecture, including bronze, silver, and gold layers.
Strong experience in dimensional modeling, data warehouse design, and reporting data layers.
Experience with batch processing, streaming, incremental loads, and change data capture.
Knowledge of data quality, governance, lineage, metadata management, reconciliation, and observability.
Experience with CI/CD, source control, automated deployment, and environment management.
Excellent communication, presentation, stakeholder-management, and customer-facing skills.
Ability and willingness to work onsite.
Preferred Qualifications
Bachelor's or master s degree in computer science, Information Technology, Engineering, or a related discipline.
AWS certification such as AWS Certified Solutions Architect or AWS Certified Data Engineer.
Databricks certification such as Databricks Certified Data Engineer Professional.
Experience migrating legacy ETL or data warehouse platforms to AWS and Databricks.
Experience with reporting tools such as Power BI, Tableau, or Amazon QuickSight.
Experience in onsite customer-facing architecture, consulting, or delivery roles.
Experience working in Agile or SAFe delivery environments.
