Microsoft Fabric

Cognizant

Chennai, INhybridPosted Jul 21, 2026
Posting intelligenceActively listedReposted 4×, possible evergreen/ghost posting

Skills

databricksazurespark

About the role

AIA -Pune Location Primery Skill-Microsoft Fabric

Job Summary

Sr Developer with 6 to 10 years of experience will design and optimize data solutions using LakeHouse Spark Job Definition OneLake SQL and PySpark while working in a hybrid day shift model and collaborating with cross functional teams to deliver reliable analytics that support retail banking focused initiatives and strategic decision making across the organization

Responsibilities

Design advanced data processing solutions on LakeHouse platforms that enable reliable analytics and reporting for critical business initiatives across hybrid environments

Develop scalable Spark Job Definition pipelines that process large data volumes efficiently while maintaining accuracy and consistency for downstream consumers

Build and optimize PySpark jobs that transform raw data into curated data sets supporting complex analytical models and operational dashboards for internal stakeholders

Write high quality SQL queries and stored procedures that ensure robust data extraction transformation and loading while adhering to performance and security standards

Implement data models within OneLake that unify structured and semi structured data sources to provide a single trusted view for analytics and data products

Collaborate with data engineers architects and analysts to translate business requirements into technical solutions that align with enterprise data strategies

Optimize data pipelines for performance reliability and cost efficiency by tuning Spark configurations query logic and resource utilization across environments

Implement data quality checks validation rules and monitoring processes that prevent data issues and ensure trustworthy insights for decision makers

Document technical designs data flows and operational procedures clearly so that solutions are easy to maintain enhance and troubleshoot by the wider team

Support production deployments by analyzing issues performing impact assessments and implementing stable fixes that minimize disruption to business operations

Participate in code reviews knowledge sharing sessions and continuous improvement activities that uplift engineering standards and foster a culture of technical excellence

Partner with business teams in domains such as retail banking to understand use cases and ensure data solutions deliver measurable value and positive societal impact

Adapt effectively to the hybrid work model by collaborating through digital tools coordinating with onsite and remote colleagues and maintaining clear communication

Qualifications

Demonstrate strong hands on expertise in LakeHouse architectures with a proven track record of delivering scalable and secure data solutions in enterprise settings

Exhibit advanced skills in Spark Job Definition and PySpark including experience with performance optimization fault tolerance and batch or streaming workloads

Show proficiency in SQL with the ability to design complex queries optimize execution plans and implement robust data transformations in production environments

Apply practical experience with OneLake or similar unified data platforms to consolidate disparate sources and support analytics self service and governance requirements

Bring solid experience in data engineering or development roles with six to ten years of progressive responsibility in modern data platforms and tools

Utilize knowledge of retail banking or financial services as a nice to have capability to design solutions that align with domain specific data patterns and regulatory needs

Communicate clearly with technical and non technical partners and contribute to a collaborative culture that supports ethical data use and better outcomes for customers and society

Certifications Required

Preferred certifications include Databricks Data Engineer Associate or Azure Data Engineer Associate or equivalent cloud data engineering credentials

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