Senior Data Engineer - Google Cloud

Job Title: GCP Data Engineer / Solution Architect (Contract)
Engagement Type: Contract, part-time
Duration: 3 months (extension possible)
Experience: 8–10 years
Work Mode: Remote / work from home
Commitment: 20 hours per week

About the Role
We need a senior data professional on a short-term, part-time contract. You'll combine hands-on data engineering on Google Cloud Platform with solution architecture and business analysis. You'll assess the current state, find gaps, design the target solution and write code where needed, working mostly on your own with our internal team and stakeholders.

Key Responsibilities

• Gather business and technical requirements through stakeholder workshops and turn them into solution designs.
• Do gap analysis between the current-state data landscape and the target-state requirements, then recommend remediation options and a roadmap.
• Define the solution architecture for data ingestion, processing, storage and consumption layers on GCP.
• Design and build scalable data pipelines using BigQuery, Dataflow, Dataproc, Cloud Composer (Airflow), Cloud Storage and Pub/Sub.
• Write production-quality code in Python, PySpark and SQL for data transformation, data quality checks and automation.
• Design data models (dimensional, data vault or lakehouse patterns) and optimize BigQuery performance and cost.
• Prepare architecture diagrams, design documents, gap analysis reports and handover documentation.
• Review code and designs, and advise the internal team on best practices for GCP data engineering.
• Report progress, risks and dependencies to project stakeholders regularly.

Required Skills & Qualifications

1. 8–10 years of experience in data engineering, data platforms or analytics, with at least 4 years of hands-on work on GCP.
2. Strong experience with GCP data services: BigQuery, Dataflow, Dataproc, Cloud Composer, Cloud Storage, Pub/Sub, IAM.
3. Expert-level Python and SQL, with solid hands-on experience in PySpark.
4. Proven solution architecture experience: designing end-to-end data platforms, integration patterns and non-functional requirements (security, scalability, cost).
5. Strong business analysis skills: requirement elicitation, process mapping, BRDs/FRDs and gap analysis.
6. Experience with CI/CD, Git and infrastructure-as-code (Terraform preferred).
7. Excellent communication and documentation skills; comfortable working with both business and technical stakeholders.
8. Self-driven and able to deliver independently in a remote, part-time setting.

Good to Have

• Google Cloud Professional Data Engineer or Professional Cloud Architect certification.
• Exposure to other cloud platforms (AWS, Azure) or to Snowflake or Databricks.
• Experience with data governance tools (Dataplex, Data Catalog) and data quality frameworks.
• Domain experience in BFSI, aviation, telecom or the public sector.