Responsibilities
- Design, develop, and maintain scalable ETL pipelines using Python and PySpark.
- Build and optimize data marts, data transformations, and SQL queries.
- Process structured, semi-structured, and unstructured data using large-scale data processing technologies.
- Investigate data quality issues, pipeline failures, production defects, and performance problems.
- Create unit, integration, automated, and data validation tests.
- Support development, UAT, deployments, releases, production operations, and incident resolution.
- Review logs, job results, database records, and performance metrics.
- Participate in planning, requirements discussions, code reviews, defect triage, and retrospectives.
- Document data flows, technical decisions, support procedures, and known issues.
- Recommend improvements to pipeline design, performance, testing, reliability, and maintainability.
- Collaborate with engineering, QA, business, product, and operations teams.
Requirements
- At least 5 years of experience in data engineering or software development.
- At least 5 years of Python development experience.
- At least 3 years of PySpark or Spark experience.
- At least 3 years of Oracle SQL experience, including query optimization and data analysis.
- Experience with ETL development, data marts, data warehousing, large-scale data processing, and production data support.
- Experience with Python, PySpark, Spark, SQL, Oracle, Hadoop, and Hive.
- Experience supporting the full SDLC, including UAT, deployment, bug fixes, and production support.
- Experience with Pandas, Jupyter Notebook, MapReduce, SQL and NoSQL databases, Git, automated testing, and data validation.
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
- Preferred qualifications include cloud-based data platforms, workflow orchestration, streaming, data modeling, partitioning, indexing, metadata management, data quality frameworks, monitoring, alerting, infrastructure as code, and automated release management.
- Banking or financial services data experience is preferred.
- Preferred certifications include data engineering, cloud, database, or big-data certifications.
- Ability to analyze complex data issues, collaborate with technical and business stakeholders, prioritize development and production issues, and maintain clear documentation.
Benefits
- Flexible workplace arrangements, mentoring, internal mobility, and learning and development programs are offered.
- The employer promotes an inclusive, equal-opportunity workplace and encourages applicants from diverse backgrounds.
- Employees are expected to complete training on security, data protection, SDLC, and operational procedures.
Tech Stack
Categories
About Synechron
At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our Synechron Labs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 14,000+, and has 55 offices in 20 countries within key global markets. For more information on the company, please visit our website:www.synechron.com.