Posted 02 July, 2026
Data Engineer
NR Consulting - India
Pune, Maharashtra, IN
Full Time
Reference: 26-15259-2220-1
Title: Data Engineer
Location: Pune
Exp: 3-5 Years
Job Description:
Location: Pune
Exp: 3-5 Years
Job Description:
KEY RESPONSIBILITIES
- Pipeline development: Design, build, and maintain end-to-end data pipelines for ingestion, transformation, and loading using Python and Databricks.
- SQL and data modelling: Write efficient SQL queries and scripts for data extraction, transformation, and validation across relational and cloud data stores.
- Azure data services: Build and manage pipelines leveraging Azure services including Azure Data Factory, Azure Blob Storage, and CosmosDB where applicable.
- Ad hoc data engineering: Respond to ad hoc data requests and pipeline changes raised by the Project Lead within agreed hour estimates.
- Data quality and validation: Implement checks, reconciliation steps, and logging to ensure data integrity and traceability across all pipelines.
- Orchestration and scheduling: Configure and manage job orchestration and scheduling on Databricks and Azure-native services.
- Documentation: Maintain clear technical documentation pipeline design notes, data dictionaries, runbooks to support knowledge transfer and continuity.
- Collaboration: Work closely with the Data Scientist, API Developer, and Cloud Engineer within the pod; coordinate with client stakeholders via the Project Lead only.
REQUIRED TECHNICAL SKILL-SET
| Skill Area | Tools / Platforms |
| Programming | Python (strong) data wrangling, scripting, automation |
| SQL | SQL (strong) query writing, optimisation, data validation |
| Big Data / Lakehouse | Databricks (hands-on) notebooks, Delta Lake, jobs |
| Cloud Azure | Azure Data Factory, Azure Blob Storage, CosmosDB, Azure Functions |
| Data Formats | JSON, CSV, Parquet, XML; REST API consumption |
| Version Control | Git, GitHub |
| DevOps Tooling | JIRA, Confluence (task and documentation management) |
PREFERRED SKILLS / NICE TO HAVE
- Experience with Azure Synapse Analytics or Azure Databricks Unity Catalog.
- Exposure to streaming data pipelines (Azure Event Hubs, Kafka).
- Familiarity with JFrog Artifactory for artefact management.
- Prior experience in a managed-services or POD-based delivery model.
- Domain exposure to manufacturing, automotive, or industrial data environments.