Job Summary
This hybrid role is for an experienced developer with strong skills in Python Databricks SQL Databricks Workflows and PySpark focused on building scalable data solutions and analytics pipelines. The developer will design implement and optimize data processing workflows that support business insights improve operational efficiency and contribute to impactful data driven products for global stakeholders.
Responsibilities
- Design robust data processing pipelines using Python and PySpark in Databricks to transform complex data into reliable curated datasets that enable advanced analytics and reporting across the organization.
- Develop optimized Databricks SQL queries to support performant dashboards and analytical workloads ensuring data consumers can access trusted information with minimal latency and high reliability.
- Configure and manage Databricks Workflows to orchestrate end to end data jobs ensuring timely execution effective dependency handling and consistent delivery of data assets to downstream applications.
- Implement reusable modular code components and libraries in Python that standardize data transformations and business logic leading to faster development cycles and improved maintainability.
- Collaborate closely with data engineers analysts and product teams in a hybrid work model to gather requirements validate solutions and align data products with strategic business objectives.
- Optimize PySpark jobs for performance and cost efficiency by tuning configurations managing partitioning strategies and leveraging best practices for large scale distributed processing.
- Ensure data quality and reliability by implementing validation checks error handling mechanisms and logging standards that reduce data issues and support faster troubleshooting.
- Conduct thorough unit testing integration testing and performance benchmarking for Databricks workflows to ensure stable releases and minimize disruptions to data consumers.
- Document datasets workflows and code logic in clear technical artifacts so that other team members can understand reuse and extend solutions effectively over time.
- Provide support for day shift operations by monitoring data workflows resolving production issues and proactively identifying opportunities to improve data reliability without requiring travel.
- Engage in continuous improvement by evaluating new Databricks features Python libraries and data engineering practices that can enhance scalability security and usability of data platforms.
- Collaborate with cloud and security teams to ensure that all Databricks development adheres to organizational policies governance standards and compliance requirements benefiting stakeholders and society through responsible data use.
- Participate in code reviews and knowledge sharing sessions in the hybrid work environment to promote high quality development practices and foster a culture of continuous learning and innovation.
Qualifications
- Demonstrate strong proficiency in Python programming with hands on experience in writing efficient modular and testable code for data engineering and analytics use cases.
- Exhibit solid experience in authoring and optimizing Databricks SQL queries for complex joins aggregations and analytical functions that support business reporting and data exploration.
- Show practical expertise in building scheduling and managing Databricks Workflows including job orchestration parameterization and monitoring to support dependable data operations.
- Apply deep understanding of PySpark fundamentals including RDDs DataFrames and Spark SQL along with performance tuning techniques suitable for large scale distributed data processing.
- Bring relevant experience of four to seven years in data engineering or analytics focused development roles working on hybrid work models and collaborating with cross functional teams.
- Demonstrate familiarity with version control practices testing frameworks and CI CD concepts that support reliable code deployment in modern data platforms.
- Display strong communication and problem solving skills that enable effective collaboration with technical and nontechnical partners while focusing on delivering impactful data solutions.
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.
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.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
