Lead Data Engineer

Job Title : Sr Data Engineering Lead Location : Indore, MP (Hybrid 3 Days a Week) Employment Type : Full-Time About the Role Ccube is seeking a visionary Senior Data Engineering Lead to spearhead and lead our entire Data Management practice.

In this pivotal role, you will architect, build, and scale our enterprise-grade data infrastructure, enabling data-driven decision-making across the organization.

This position calls for a strong technical foundation in distributed data systems, deep hands-on experience with modern big data and cloud technologies, and a proven track record of leading and mentoring high-performing data engineering teams.

The ideal candidate will define the data engineering roadmap, drive innovation, and deliver robust, scalable, and efficient data solutions that power Ccube’s growth and success.

Key Responsibilities

• Data Strategy & Architecture ○ Define the end-to-end data engineering strategy and technical vision aligned with Ccube’s business goals.
• ○ Architect scalable, high-performance, and cost-efficient data platforms Preferably on (AWS, Azure) or GCP.
• ○ Design and optimize data Lakehouse medallion architectures integrating batch and streaming pipelines (Spark, Kafka, Delta Lake, Iceberg, Hudi, etc.).
• ○ Build reusable frameworks for data ingestion, transformation, and orchestration across heterogeneous systems.
• Data Engineering Execution ○ Lead the development and optimization of ETL / ELT pipelines using PySpark, Scala, SQL, and Airflow or equivalent orchestration tools.
• ○ Oversee the implementation of real-time streaming solutions leveraging Kafka, Kinesis, or Pub / Sub.
• ○ Guide the team in integrating structured, semi-structured, and unstructured data sources.
• ○ Drive adoption of DataOps and DevOps best practices — CI / CD for data pipelines, automated testing, and monitoring .
• Cloud & Infrastructure ○ Design and manage cloud-native data solutions (AWS Glue, EMR, Redshift, Snowflake, BigQuery, Databricks, etc.) ○ Lead initiatives for data platform modernization and cloud migration strategies.
• Governance, Security & Observability ○ Define and enforce standards for data quality, lineage, governance, and metadata management (e.g., Great Expectations, Apache Atlas, or Collibra).
• ○ Implement robust data security, compliance, and privacy frameworks aligned with industry standards (GDPR, HIPAA, etc.).
• ○ Establish observability frameworks for data pipelines — logging, monitoring, and anomaly detection.
• Leadership & Collaboration ○ Lead and mentor a team of senior and mid-level data engineers, fostering a culture of excellence, ownership, and innovation.
• ○ Collaborate cross-functionally with AI / ML, Analytics, and Product Engineering teams to enable data-driven decision-making.
• ○ Evaluate emerging technologies (e.g., VectorDBs, GraphDBs, RAG frameworks) and drive their adoption for advanced data-driven use cases.

○ Represent the data engineering practice in architecture reviews and executive technology forums.

Required Qualifications

○ Strong experience with big data ecosystems (Hadoop, Hive, Presto, Trino, Delta Lake, etc.).

Proven hands-on work in cloud data platforms – AWS (Glue, EMR, Redshift), GCP (Dataflow, BigQuery), or Azure (Synapse, Data Factory).