Data Engineering Lead

Client: Corover.ai

Hiring: Data Engineering Lead

Experience: 8–12 years

Educational Qualification

• B.Tech./M.Tech./M.S. in Computer Science, Data Engineering, or a related field.

Mandatory Experience

• 8–12 years in data engineering or data platform architecture.
• At least 4–5 years designing and managing large-scale data pipelines.
• 5–7 years designing and implementing enterprise data architectures for analytics and AI/ML.
• Experience working with structured, semi-structured, and unstructured data.

Mandatory Technical Skills

• Cloud services: AWS Redshift, Glue, S3; Azure Synapse; GCP BigQuery and Dataflow.
• Big data: Apache Spark, Hadoop, Kafka, Airflow, Databricks, Snowflake, and dbt.
• Programming: Python, Scala, Java, and SQL.
• Databases: PostgreSQL, MongoDB, Cassandra, and Elasticsearch.
• Data management: ETL/ELT design, schema evolution, DataOps, and CI/CD pipelines.
• Infrastructure: Docker, Kubernetes, Terraform, and Jenkins.
• Governance: Data cataloguing, lineage, access control, encryption, and compliance logging.

Key Responsibilities

• Architect scalable data pipelines for AI/ML models and analytical workloads.
• Design data lakes and data warehouses.
• Build batch and real-time data ingestion frameworks.
• Implement metadata management, lineage tracking, and data governance.
• Optimize data storage, compression, retrieval, and pipeline performance.
• Ensure high-quality, versioned datasets and compliance with applicable data privacy and retention policies.

Preferred: AWS, Azure, or GCP data platform certifications.

Pay: ₹2,300,000.00 - ₹3,800,000.00 per year

Application Question(s):

• How many years of overall experience do you have in Data Engineering?

• How many years of experience do you have designing and managing large-scale data pipelines?

• Do you have experience designing enterprise data architectures for analytics and AI/ML workloads?

• Which cloud data platforms have you worked with?

• Do you have hands-on experience with Apache Spark, Kafka, Airflow, Databricks, Snowflake, or dbt?

• Are you proficient in Python and SQL for data engineering?

• Do you have experience designing data lakes, data warehouses, and batch/real-time data pipelines?

• Do you have experience with ETL/ELT, DataOps, and CI/CD pipelines?

• Do you have experience implementing data governance, data lineage, security, and access controls?

• Have you led a data engineering team?

• Current CTC

• Expected CTC

• How soon can you join?

Work Location: In person