Lead Data Engineer - R01553055

Lead Data Engineer Primary Skills GCP, Big Query, Python, Airflow, SQL, DBT Job requirements About the Role We are seeking a Senior Data Engineer with deep expertise in Google Cloud Platform (GCP) and BigQuery to lead cloud modernization initiatives, develop scalable data pipelines, and enable real-time data processing for enterprise-level systems. This is a high-impact role focused on driving the transformation of legacy infrastructure into a robust, cloud-native data ecosystem. Key Responsibilities 1. Data Migration & Cloud Modernization Analyze legacy on-premises and hybrid cloud data warehouse environments (e.g., SQL Server). Lead the migration of large-scale datasets to Google BigQuery . Design and implement data migration strategies ensuring data quality , integrity , and performance . 2. Data Integration & Streaming Integrate data from various structured and unstructured sources, including APIs , relational databases , and IoT devices . Build real-time streaming pipelines for large-scale ingestion and processing of IoT and telemetry data. 3. ETL / Data Pipeline Development Modernize and refactor legacy SSIS packages into cloud-native ETL pipelines . Develop scalable, reliable workflows using Apache Airflow , Python , Spark , and GCP-native tools . Ensure high-performance data transformation and loading into BigQuery for analytical use cases. 4. Programming & Query Optimization Write and optimize complex SQL queries , stored procedures, and scheduled jobs within BigQuery. Develop modular , reusable transformation scripts using Python , Java , Spark , and SQL. Continuously monitor and optimize query performance and cost efficiency in the cloud data environment. Required Skills & Experience 5+ years in Data Engineering with a strong focus on cloud and big data technologies. Minimum 2+ years of hands-on experience with GCP , specifically BigQuery . Proven experience migrating on-premise data systems to the cloud . Strong development experience with Apache Airflow , Python , and Apache Spark . Expertise in streaming data ingestion , particularly in IoT or sensor data environments. Strong SQL development skills; experience with BigQuery performance tuning . Solid understanding of cloud architecture , data modeling , and data warehouse design . Familiarity with Git and CI/CD practices for managing data pipelines. Preferred Qualifications GCP Professional Data Engineer certification. Experience with modern data stack tools like dbt , Kafka , or Terraform . Exposure to ML pipelines , analytics engineering , or DataOps/DevOps methodologies. Why Join Us? Work with cutting-edge technologies in a fast-paced, collaborative environment. Lead cloud transformation initiatives at scale. Competitive compensation and benefits. Remote flexibility and growth opportunities.