•••• is serving as a trusted IT Outsourcing partner in line with the needs of World's most prestigious firms and carried out successful projects worldwide.
Responsibilities:
Design, develop, and maintain automated data ingestion and ELT/ETL integration pipelines from source systems.
Build and support scalable data products and API-based data services.
Collaborate with business stakeholders, subject-matter experts, and cross-functional squads to understand business domains and legacy systems.
Advise stakeholders on technical trade-offs, architecture decisions, and data solution design.
Partner with data architects and stewards to enforce data governance, quality baselines, security, and scalability.
Make independent architectural and tooling decisions in coordination with product owners.
Mentor team members and promote engineering best practices across data modeling and pipeline architecture.
Implement testing strategies, automated validation gates, and CI/CD pipelines for reliable code delivery.
Skills:
4+ years of professional experience designing data warehouse solutions and end-to-end data products.
Advanced proficiency in Python and complex SQL for large-scale data processing.
Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, Azure Data Factory, or Delta Lake.
Proven track record architecting and deploying scalable data platforms on Microsoft Azure.
Strong knowledge of data modeling (dimensional modeling, Data Vault, or medallion architecture) and cloud cost optimization.
Experience implementing automated testing and CI/CD workflows for data platforms.
Strong communication skills and independence in a distributed, agile environment.
Nice to Have:
Experience with Master Data Management (MDM) tools and data governance practices.
Practical background in designing and developing RESTful APIs or data-serving layers.
Familiarity with modern data platform governance, cataloging, and lineage tools (e.g., Microsoft Purview, Unity Catalog).
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