Job Summary

seeking an experienced Data Engineer to design, develop, and optimize scalable enterprise data pipelines and transformation solutions on Google Cloud Platform (GCP).

Key Responsibilities

Data Engineering & Development

• Design and develop scalable data ingestion, transformation, and processing pipelines on GCP.
• Build reusable engineering frameworks and patterns for batch, incremental, and Change Data Capture (CDC) workloads.
• Develop and maintain data transformations using BigQuery, Dataform, SQL, and Python.
• Convert business and technical requirements into efficient data engineering solutions.
• Support high-volume enterprise data migration and modernization initiatives.

GCP Data Platform

• Design and implement solutions using GCP services such as:
• BigQuery
• Cloud Storage
• Pub/Sub
• Dataflow
• Dataproc
• Cloud Composer
• Dataform
• Optimize BigQuery datasets, queries, partitioning, clustering, and overall workload performance.

Data Integration & CDC

• Design and implement batch and near-real-time data integration patterns.
• Build CDC pipelines from enterprise source systems into GCP.
• Handle inserts, updates, deletes, schema changes, incremental loads, and error/reprocessing scenarios.
• Experience with CDC/integration technologies such as Qlik Replicate/Qlik CDC, Datastream, Informatica, or equivalent is advantageous.

Data Quality & Reconciliation

• Implement data validation and reconciliation between source and target systems.
• Develop automated controls covering row counts, duplicates, nulls, aggregates, business rules, and transformation accuracy.
• Troubleshoot data discrepancies and work with source-system, QA, and business teams to resolve issues.
• Support SIT, UAT, migration rehearsals, production cutover, and hypercare.

DevOps & Automation

• Implement CI/CD practices for data engineering workloads.
• Maintain source code and deployment artifacts using Git/GitHub.
• Integrate automated testing and deployment into pipelines using tools such as GitHub Actions, Cloud Build, Jenkins, or equivalent.
• Promote reusable coding standards, parameterized solutions, and automated deployments across environments.

Technical Leadership

• Provide technical guidance and mentoring to junior data engineers.
• Review solution designs, code, SQL, transformation logic, and deployment artifacts.
• Define reusable patterns and data engineering best practices.
• Collaborate with Data Architects, Platform Engineers, Data Modelers, DBAs, QA teams, and business stakeholders.
• Support technical troubleshooting and root-cause analysis of complex data issues.

Skill Requirements

Core skills

• Google Cloud Platform (GCP)
• BigQuery
• Dataform
• Advanced SQL
• Python
• Data integration / ETL / ELT
• CDC patterns
• Data modeling concepts
• Git / GitHub
• CI/CD
• Data reconciliation and testing

Other Requirements

• 5- 9 years of overall data engineering/ETL experience with strong hands-on cloud data engineering expertise.
• Strong experience working with large datasets and complex SQL transformations.
• Experience delivering enterprise data migration, modernization, or analytics solutions.
• Strong analytical, troubleshooting, communication, and stakeholder-management skills.

Preferred Certifications

• Google Cloud Professional Data Engineer