Senior Data Engineer
About this role
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Skills you'll use
What you'll do
- Design and implement scalable batch and streaming data pipelines on GCP.
- Build and maintain data solutions using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and related services.
- Architect robust data models for analytics, BI, and AI/ML use cases.
- Lead technical discussions and mentor junior data engineers.
- Optimize data processing performance, cost, and reliability.
- Implement CI/CD, DevOps, and Infrastructure-as-Code practices.
- Collaborate with data architects, analysts, and business stakeholders to deliver high-quality solutions.
- Ensure data governance, security, and compliance standards are followed.
Who can apply
- 6–9 years of experience in Data Engineering or Data Platform development.
- Strong hands-on experience with GCP services: BigQuery, Dataflow (Apache Beam), Dataproc / Spark, Pub/Sub, Cloud Composer (Airflow)
- Advanced Python and SQL skills.
- Expertise in building ETL/ELT pipelines and data modeling.
- Experience with distributed processing frameworks (Spark preferred).
- Strong understanding of Data Lakehouse architecture.
- Experience with Azure Data Factory (ADF) or Azure data ecosystem.
- Knowledge of Terraform or other IaC tools.
- Exposure to ML/AI data pipelines.
- Experience with containerization (Docker/Kubernetes).
- Familiarity with BI tools such as Power BI or Looker.
- Strong leadership and mentoring ability.
- Excellent communication and stakeholder management.
- Ability to work in fast-paced, Agile environments.
Perks & benefits
Interview & selection process
3 rounds — typical selection flow for this role:
- 1Apply — submit your profile through SRKay's online portal
- 2Screen — initial review and comprehensive phone screening
- 3Interview — technical assessments and cultural-fit interviews
- 4Offer
About SRKay Consulting Group
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