Job Summary
Serve as a senior technical expert acting as a lead developer in data engineering initiatives that use SQL Azure Databricks Azure Data Lake Store and Azure Data Factory to build scalable data solutions in a hybrid work model. Contribute to high quality data platforms that support investment banking focused analytics and operational reporting in a collaborative day shift environment.
Responsibilities
Design robust data engineering solutions using SQL Azure Databricks Azure Data Lake Store and Azure Data Factory to deliver secure and scalable data pipelines for complex analytics needs in investment banking contextsDevelop efficient batch and near real time data pipelines that ingest transform and curate structured and semi structured data to enable high quality downstream reporting and regulatory analysisImplement optimized SQL queries stored procedures and data models that improve query performance reduce compute cost and ensure reliable data access for analytical users and operational teamsConfigure and maintain Azure Databricks clusters notebooks and jobs to orchestrate data transformations while managing resource utilization and promoting consistent engineering practicesBuild and manage Azure Data Factory pipelines triggers and activities to automate data movement across diverse sources and sinks while enforcing standardized patterns and reusable componentsAdminister Azure Data Lake Store structures access patterns and data lifecycle policies to ensure organized storage cost effectiveness and secure handling of sensitive financial informationCoordinate with business analysts and stakeholders from investment banking operations to translate requirements into precise technical specifications and data transformations that align with business objectivesCollaborate with quality engineering and operations teams to design validation checks reconciliation controls and monitoring processes that ensure data completeness accuracy and timelinessGuide peers on best practices in coding testing documentation and version control to maintain high engineering standards and consistent delivery of maintainable data solutionsPerform root cause analysis for data issues production incidents and performance bottlenecks then implement durable fixes and preventive improvements that enhance platform stabilityDocument solution designs data flow diagrams data dictionaries and operational runbooks in clear language so that cross functional teams can easily understand maintain and extend the platformsEngage with architecture and security teams to align implementations with enterprise reference patterns compliance expectations and resiliency objectives across the Azure data platformParticipate in sprint planning backlog refinement and technical reviews to ensure that stories are scoped realistically risks are identified early and deliverables meet quality expectations for stakeholders
Qualifications
Combine extensive hands on experience in SQL Azure Databricks Azure Data Lake Store and Azure Data Factory with an ability to design end to end data pipelines that support analytics for financial servicesApply knowledge of investment banking operations or investment banking and brokerage processes when available to shape data models transformation rules and controls that reflect real world trade and post trade workflowsDemonstrate strong understanding of data warehousing concepts dimensional modeling and performance tuning methods that support high volume and low latency analytical workloadsUtilize experience with hybrid working environments and cross functional collaboration tools to maintain clear communication effective documentation and timely delivery across distributed teamsExhibit solid problem solving skills attention to detail and a continuous improvement mindset that support reliable production operations and incremental enhancement of the data platform
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
Applicants for US based positions must be currently authorized to work for any employer in the United States. The company is unable to provide employment-based immigration sponsorship for US based positions.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] for roles based in the Americas or [email protected] for roles based in India.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
