Senior Data Engineer

Project description

As part of Client Technology team, the data Engineer will work to design, develop, and support scalable data solutions that underpin strong engineering practices, implicit data controls and the functional requirements for effective surveillance and regulatory reporting use cases. The scope will focus on onboarding new data sources, developing data ingestion and transformation pipelines, implementing data quality controls, supporting lineage and metadata requirements, and enabling efficient management of transactional and non-transactional/ reference data across the platform. The role will support both strategic initiatives and ongoing operational requirements

Responsibilities

• Data Pipeline Development: Design, build, and maintain scalable batch and real-time streaming data pipelines (ETL/ELT) using tools like Dataflow, Pub/Sub, and Dataproc.
• Data Warehousing & Modeling: Architect and optimize enterprise data warehouses, data lakes, and dimensional models inside BigQuery, Cloud Storage, and Cloud SQL.
• Performance & Cost Optimization: Tune query performance, configure proper partitioning and clustering, and manage data lifecycle/retention policies.
• Data Governance & Security: Enforce security controls, encryption, access management, and automated data quality checks.
• Automation & DevOps: Implement Infrastructure as Code (Terraform) and CI/CD pipelines via GitHub or cloud-native deployment tools.

SKILLS

Must have

• Minimum of 8 years of experience in data engineering, with a strong focus on SQL and data manipulation.
• Cloud Platform: Deep experience with GCP services including BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc, and Cloud Composer.
• Programming & Query Languages: Proficiency in Python, SQL, Java, Scala, or Golang.
• Big Data & Analytics Concepts: Data modeling, star schemas, slowly changing dimensions (SCD), Apache Beam, and dbt.
• Education & Experience: Typically a Bachelor’s or Master’s degree in Computer Science or Engineering,

Nice to have

Banking

Responsibilities

• • Data Pipeline Development: Design, build, and maintain scalable batch and real-time streaming data pipelines (ETL/ELT) using tools like Dataflow, Pub/Sub, and Dataproc. • Data Warehousing & Modeling: Architect and optimize enterprise data warehouses, data lakes, and dimensional models inside BigQuery, Cloud Storage, and Cloud SQL. • Performance & Cost Optimization: Tune query performance, configure proper partitioning and clustering, and manage data lifecycle/retention policies. • Data Governance & Security: Enforce security controls, encryption, access management, and automated data quality checks. • Automation & DevOps: Implement Infrastructure as Code (Terraform) and CI/CD pipelines via GitHub or cloud-native deployment tools.