Responsibilities

This Data Engineer will shape large-scale data architecture vision and roadmap across client engagements, establish governance, security frameworks, and regulatory compliance standards, lead strategy around platform selection, integration, and scaling, guide organizations in adopting data lakehouse and federated data models, lead technical discovery sessions to understand client needs, translate complex architectures into clear, actionable value for stakeholders, build trusted advisor relationships and guide strategic decisions, design and implement modern data lakehouse architectures with Delta Lake and Databricks, build and manage ETL/ELT pipelines at scale using Spark (PySpark preferred), leverage Delta Live Tables, Unity Catalog, and schema evolution features, optimize storage and queries on cloud object storage (e.g., AWS S3, Azure Data Lake), integrate with cloud-native services like AWS Glue, GCP Dataflow, and Azure Synapse Analytics, implement data quality monitoring, lineage tracking, and schema versioning, and build scalable pipelines with tools like Apache Airflow, Step Functions, and Cloud Composer.