Live opening · Posted 1 day ago

Senior Data Engineer (Databricks)

Stancecode Technology Private Limited · Pune Division, Maharashtra, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyStancecode Technology Private Limited
LocationPune Division, Maharashtra, India (On-site)
Work modeNo
SkillsPython, Azure
SourceLinkedin
ListedPosted 1 day ago

About the role

Description supplied by the original job listing.

Company Description: Stancecode Technology Private Limited is a specialized IT consulting firm focused on delivering tailored digital solutions that help organizations grow and transform. The team combines expertise in business development, growth strategies, cloud, DevOps, AI, and turnkey bid management to support clients across public and private sectors. By aligning technology with business goals, Stancecode enables companies to optimize their systems, scale efficiently, and enhance performance. The firm’s mission is to drive sustainable growth and innovation through strategic IT consulting and seamless technology integration, offering opportunities for team members to work on impactful, end-to-end solutions.
Key Responsibilities and Requirements
Databricks and Python: Extensive hands-on experience building, optimising, and maintaining data pipelines and transformations in Databricks (Spark, Delta Lake) using Python/PySpark.
Azure cloud services: Solid experience with Azure data services, particularly Azure Data Factory for orchestration and ETL/ELT workflows, and Azure Functions for serverless, event-driven processing.
Advanced SQL: Very strong SQL skills, including complex queries, performance tuning, window functions, and stored procedures, across large-scale datasets.
Dimensional data modelling: Proven expertise in designing data warehouses and data marts using Kimball methodology, including star/snowflake schemas, fact and dimension tables, slowly changing dimensions (SCDs), and conformed dimensions.
Business analysis: Ability to gather and translate business requirements into technical specifications, work with stakeholders, and define data requirements, KPIs, and reporting needs.
Data quality and delivery: Ownership of end-to-end solution delivery, including data validation, testing, documentation, and adherence to best practices for scalability, security, and reliability.
AI-assisted development: Comfortable working with Databricks Genie, Claude, and GitHub Copilot to accelerate development, query writing, debugging, and documentation, while validating AI-generated output for accuracy and quality.
Experience required: 5-10 years in data engineering and analytics

Work arrangement
No

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