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.
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• 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.
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• 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.
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• 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.
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• 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.