Key Responsibilities

Cloud Migration & Modernization

Analyze and assess legacy on-premise and hybrid data warehouse systems (e.g., SQL Server)
Lead large-scale migration of datasets to Google BigQuery
Define and implement migration strategies ensuring data quality, integrity, and performance optimization

Data Pipeline & ETL Development

Design and build scalable ETL/ELT pipelines using Python, Apache Airflow, Spark, and GCP-native services
Modernize legacy ETL systems (e.g., SSIS) into cloud-native workflows
Ensure reliable and efficient data ingestion, transformation, and loading into BigQuery

Data Integration & Streaming

Integrate data from multiple sources including APIs, relational databases, IoT, and unstructured data systems
Build real-time streaming pipelines for high-volume IoT and telemetry data processing
Ensure low-latency, scalable, and fault-tolerant data ingestion systems

SQL Development & Performance Optimization

Write and optimize complex SQL queries, stored procedures, and scheduled jobs in BigQuery
Improve query performance and optimize cost efficiency in cloud environments
Develop reusable and modular transformation logic using SQL, Python, and Spark

Cloud Data Architecture

Design scalable data warehouse and lakehouse architectures on GCP
Implement best practices for data modeling, partitioning, and performance tuning
Ensure adherence to modern cloud architecture principles and scalability requirements

DevOps, CI/CD & DataOps Practices

Implement CI/CD pipelines for data workflows using Git and modern DevOps practices
Ensure version control, deployment automation, and pipeline reliability
Collaborate with DevOps teams for production-grade data systems

Leadership & Collaboration

Work closely with architects, analysts, and business stakeholders to define data solutions
Provide technical leadership and mentorship to engineering teams
Drive best practices in cloud data engineering, DataOps, and analytics engineering

Innovation & Modern Data Stack

Work with tools such as dbt, Kafka, Terraform, and modern data stack technologies
Explore ML pipelines and advanced analytics engineering use cases
Continuously improve data engineering processes and platform efficiency

Lead Data Engineer - R01553055