About the role
Designation : Senior Analyst - Data Engineering
Level : L2
Location : Chennai, Tamil Nadu , India
Experience : 3 to 5 years
Job Role :
- 3+ years of experience delivering enterprise cloud data engineering solutions.
- Strong programming skills in Python and SQL.
- Experience supporting AI/ML, GenAI, Retrieval-Augmented Generation (RAG), semantic search, feature engineering, or model monitoring.
- Experience working with unstructured data (documents, logs, images, text, transcripts, and embeddings).
- Hands-on experience with BigQuery, Spark, Dataflow, Dataproc, Airflow/Cloud Composer, DBT, or Dataform.
- Hands-on experience with MLOps, pipeline observability, and production incident management.
- Experience building scalable batch and streaming data pipelines.
- Knowledge of DataOps practices, including Git, CI/CD, automated testing, and version control.
- Experience migrating legacy Hadoop or on-premises platforms to cloud-native environments.
- Knowledge of APIs, microservices, event-driven architectures, streaming data, and real-time analytics.
- Cloud certifications in GCP, AWS, or Azure.
- Experience mentoring junior engineers and contributing to engineering standards.
Responsibilities :
- Translate business, analytics, and AI use cases into scalable data engineering solutions.
- Design, develop, and maintain batch and streaming data pipelines.
- Build reusable, production-grade data products for analytics, BI, ML, and GenAI applications.
- Develop high-quality ETL/ELT pipelines using Python and SQL.
- Utilize cloud-native technologies such as BigQuery, Dataflow, Dataproc, Spark, Airflow/Cloud Composer, DBT, and Dataform.
- Implement data quality validation, monitoring, metadata management, lineage, and observability.
- Enable AI/ML and GenAI teams by preparing feature datasets, vector-ready datasets, and governed data assets.
- Optimize pipeline performance, storage utilization, cloud cost, and system reliability.
- Apply DataOps practices, including CI/CD, automated testing, version control, and release management.
- Support data governance, security, privacy, access control, and regulatory compliance.
- Collaborate with Data Scientists, ML Engineers, Product Owners, and business stakeholders.
- Troubleshoot production issues and continuously improve platform stability and performance.
Required skills :
Python - SQL / BigQuery - Google Cloud Platform (GCP) - Data Engineering (ETL/ELT & Data Pipelines) - Spark / Dataflow / Dataproc,- Airflow / Cloud Composer - DBT / Dataform - Git & CI/CD (DataOps) - AI/ML & GenAI Data Engineering - Data Quality, Governance & Monitoring.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.