Senior Data Engineer

Job Description:

Job Title: Lead GCP Data Engineer (Senior Level)

Reports to: SVP, Head of Data, Technology & Analytics
Location: Remote – Global (must be available through 2 p.m. U.S. Eastern Time)
Employment Type: Full-time • Long-term Contract (Annual Renewal)

Key Responsibilities

Data Engineering & Development

• Design, build, and optimize scalable ELT/ETL pipelines to process structured and unstructured data across batch and streaming systems.
• Architect and deploy cloud-native data workflows using GCP services including BigQuery, Cloud Storage, Cloud Functions, Cloud Pub/Sub, Dataflow, and Cloud Composer.
• Build high-throughput Apache Spark workloads in Python and SQL, with performance tuning for scale and cost.
• Develop parameterized DAGs in Apache Airflow with retry logic, alerting, SLA/SLO enforcement, and robust monitoring.
• Build reusable frameworks for high-volume API ingestion, transforming Postman collections into production-ready Python modules.
• Translate business and product requirements into scalable, efficient data systems that are reliable and secure.

Cloud Infrastructure & Security

• Implement IAM and VPC-based security to manage and deploy GCP infrastructure for secure data operations.
• Ensure robustness, scalability, and cost-efficiency of all infrastructure, following FinOps best practices.
• Apply automation through CI/CD pipelines using tools like Git, Jenkins, or Bitbucket.

Data Quality, Governance & Optimization

• Design and implement data quality frameworks, monitoring, validation, and anomaly detection.
• Build observability dashboards to ensure pipeline health and proactively address issues.
• Ensure compliance with data governance policies, privacy regulations, and security standards.

Collaboration & Project Delivery

• Work closely with cross-functional stakeholders including data scientists, analysts, DevOps, product managers, and business teams.
• Effectively communicate technical solutions to non-technical stakeholders.
• Manage multiple concurrent projects, shifting priorities quickly and delivering under tight timelines.
• Collaborate within a globally distributed team with real-time engagement through 2 p.m. U.S. Eastern Time.

Qualifications & Certifications

Education

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.

Experience

• Minimum 7+ years in data engineering with 5+ years of hands-on experience on GCP.
• Proven track record with tools and services like BigQuery, Cloud Composer (Apache Airflow), Cloud Functions, Pub/Sub, Cloud Storage, Dataflow, and IAM/VPC.
• Demonstrated expertise in Apache Spark (batch and streaming), PySpark, and building scalable API integrations.
• Advanced Airflow skills including custom operators, dynamic DAGs, and workflow performance tuning.

Certifications

• Google Cloud Professional Data Engineer certification preferred.

Key Skills

Mandatory Technical Skills

• Advanced Python (PySpark, Pandas, pytest) for automation and data pipelines.
• Strong SQL with experience in window functions, CTEs, partitioning, and optimization.
• Proficiency in GCP services including BigQuery, Dataflow, Cloud Composer, Cloud Functions, and Cloud Storage.
• Hands-on with Apache Airflow, including dynamic DAGs, retries, and SLA enforcement.
• Expertise in API data ingestion, Postman collections, and REST/GraphQL integration workflows.
• Familiarity with CI/CD workflows using Git, Jenkins, or Bitbucket.
• Experience with infrastructure security and governance using IAM and VPC.

Nice-to-Have Skills

• Experience with Terraform or Kubernetes (GKE).
• Familiarity with data visualization tools such as Looker or Tableau.
• Exposure to MarTech/AdTech data sources and campaign analytics.
• Knowledge of machine learning workflows and their integration with data pipelines.
• Experience with other cloud platforms like AWS or Azure.

Soft Skills

• Strong problem-solving and critical-thinking abilities.
• Excellent verbal and written communication skills to engage technical and non-technical stakeholders.
• Proactive and adaptable, with a continuous learning mindset.
• Ability to work independently as well as within a collaborative, distributed team.

Working Hours

• Must be available for real-time collaboration with U.S. stakeholders every business day through 2 p.m. U.S. Eastern Time (minimum 4-hour overlap).

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