Data Engineer -

Band: B3

Primary Skills: 1) PySpark / Scala Spark 2) Databricks 3) Airflow/ Autosys/ ADF (any orchestration tool) 4) CI/CD 5)ETL

JC: 148750

NP: immediate to 45 days

Job Loc: Pune Kharadi (3 days WFO)

Role Overview

We are seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines and platforms within UBS's cloud‑based analytics ecosystem. The role requires strong expertise in distributed data processing using Spark, Azure Databricks, and Azure Data Factory, along with solid engineering practices and collaboration within Agile teams.

Key Responsibilities & Expertise

Core Data Engineering Skills

Design and develop robust data pipelines handling structured, semi‑structured, and unstructured data, enabling efficient data ingestion, transformation, and analytics.

Extract insights and identify relationships across disparate data sources to support business and analytical use cases.

Build and optimize distributed data processing solutions using Apache Spark (Databricks preferred) with PySpark and/or Scala.

Programming & Data Processing

Hands-on experience in Python and/or Scala, with strong proficiency in Spark‑based data transformations.

Good working knowledge of Python data libraries such as pandas and scikit‑learn for data preparation and basic machine‑learning workflows.

Strong SQL expertise, including complex query authoring, performance tuning,



and working with large datasets.

Data Platforms & Azure Ecosystem

Experience working with Azure Databricks, Azure Data Factory, and Azure Data Lake Storage (ADLS Gen2).

Experience with broader Azure data and storage services, including Azure SQL and other data services.

Exposure to traditional data warehousing concepts and contemporary cloud‑based data architectures.

Experience with Azure DevOps for source control, CI/CD pipelines, and release management.

Exposure to Stonebranch UAC for data pipeline orchestration.

Databases & Storage Technologies

Hands-on experience with at least two database technologies, including:

Relational Databases (RDBMS): PostgreSQL, MS SQL Server, Oracle

NoSQL Databases: Cosmos DB, MongoDB, Cassandra, Neo4j, Gremlin

Ability to design and query data models optimized for analytics and large‑scale processing.

Engineering Practices

Proficient in managing large and complex codebases using GitHub, following GitFlow and Fork/Pull Request models.

Strong understanding of CI/CD best practices for data engineering workloads.

Experience working in Agile delivery models, including Scrum, XP, and Kanban.

Nice to Have (Preferred)

Exposure to web services development using REST and/or SOAP APIs.

Experience with Azure IoT Hub / IoT Central.

Working knowledge of Azure Kubernetes Service (AKS) and containerized workloads.

📌 Azure Data Engineer (Pune)
🏢 TalentOla
📍 Pune