Endava - Data Engineer - Python/SQL/ETL

2 weeks ago

Bengaluru, Karnataka, India Hirist Full time

Note : If shortlisted, you will be invited for initial rounds on 13th September'25 (Saturday) in : Data Engineer

Experience Level : 5-10 years

A Data Engineer will designs, implements, and optimizes scalable data pipelines and architectures. This role will bridge raw data and actionable insights, ensuring robustness, performance, and data governance.

Collaboration with analysts and scientists is central to delivering high-quality solutions aligned with business objectives.

Key Responsibilities :

Data Pipeline Development :

- Architect, implement and maintain real-time and batch data pipelines to handle large datasets efficiently.

- Employ frameworks such as Apache Spark, Databricks, Snowflake or Airflow to automate ingestion, transformation, and delivery.

Data Integration & Transformation :

- Work with Data Analysts to understand source-to-target mappings and quality requirements.

- Build ETL/ELT workflows, validation checks, and cleaning steps for data reliability.

Automation & Process Optimization :

- Automate data reconciliation, metadata management, and error-handling procedures.

- Continuously refine pipeline performance, scalability, and & Leadership :

- Coordinate with Data Scientists, Data Architects, and Analysts to ensure alignment with business goals.

- Mentor junior engineers and enforce best practices (version control, CI/CD for data pipelines).

- Participate in technical presales activities and client engagement initiatives.

Governance & Compliance :

- Apply robust security measures (RBAC, encryption) and ensure regulatory compliance (GDPR).

- Document data lineage and recommend improvements for data ownership and stewardship.

Qualifications :

Programming :

- Python, SQL, Scala, Java.

Big Data :

- Apache Spark, Hadoop, Databricks, Snowflake, etc.

Cloud :

- AWS (Glue, Redshift), Azure (Synapse, Data Factory, Fabric), GCP (BigQuery, Dataflow).

Data Modelling & Storage :

- Relational (PostgreSQL, SQL Server), NoSQL (MongoDB, Cassandra), Dimensional modelling.

DevOps & Automation :

- Docker, Kubernetes, Terraform, CI/CD pipelines for data flows.

Architectural Competencies :

1. Data Modelling :

- Designing dimensional, relational, and hierarchical data models.

2. Scalability & Performance :

- Building fault-tolerant, highly available data architectures.

3. Security & Compliance :

- Enforcing role-based access control (RBAC), encryption, and auditing.

(ref:hirist.tech)

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