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

📌 Data Engineering Lead (Delhi)
🏢 Spinode Technologies
📍 Delhi