Job Summary Synechron is seeking a Data Engineer with 5+ years of experience building data marts, ETL pipelines, and large-scale data processing solutions. The role will develop reliable data products using Python, PySpark, SQL, and data warehousing technologies while supporting the full software development lifecycle. Software Requirements Required Python: 5+ years of development experience. PySpark/Spark: 3+ years of experience. Oracle SQL: 3+ years, including query optimization and data analysis. Pandas and Jupyter Notebook. ETL development and data warehousing. Hadoop, Hive, and MapReduce. SQL and NoSQL databases. Git, CI/CD tools, automated testing, and data validation. Experience supporting development, UAT, production deployment, and production issues. Preferred Cloud-based data platforms. Workflow orchestration tools. Data quality and monitoring tools. Banking or financial services data experience. Overall Responsibilities Design, develop, and maintain scalable ETL pipelines using Python and PySpark. Build and optimize data marts and transformation processes. Process structured, semi-structured, and unstructured data. Analyze and resolve data issues using Oracle SQL, PySpark, and data analysis techniques. Support development, testing, UAT, deployment, and production operations. Collaborate with engineering, QA, business, and operations teams. Apply coding standards, testing practices, and CI/CD processes. Improve data quality, pipeline performance, reliability, and maintainability. Technical Skills (By Category) Programming Languages Essential: Python, PySpark, Spark, SQL, and Pandas. Preferred: Scala or another data-processing language. Databases and Data Management Essential: Oracle, SQL and NoSQL databases, data marts, data warehousing, ETL, data validation, and query optimization. Preferred: Data modeling, partitioning, indexing, metadata management, and data quality frameworks. Cloud Technologies Essential: Understanding of distributed data environments and production data platforms. Preferred: Experience with cloud storage, compute, managed Spark services, and cloud data warehouses. Frameworks and Libraries Essential: PySpark, Apache Spark, Pandas, Hadoop, Hive, MapReduce, and Jupyter Notebook. Preferred: Workflow orchestration, streaming, and data quality frameworks. Development Tools and Methodologies Essential: Git, CI/CD, Agile delivery, code reviews, automated testing, debugging, deployment, and production support. Preferred: Infrastructure as code, monitoring, alerting, and automated release management. Security Protocols Essential: Secure handling of data, access controls, secrets management, encryption, and data privacy practices. Preferred: Experience with audit controls and regulated data environments. Experience Requirements 5+ years of experience in data engineering or software development. Proven experience developing ETL pipelines, data marts, and large-scale data processing solutions. Experience with Python, PySpark, Spark, SQL, Oracle, Hadoop, and Hive. Experience supporting the complete SDLC, including UAT, deployment, bug fixes, and production support. Banking or financial services experience is preferred. Equivalent experience in data development, analytics engineering, platform engineering, or production data support may be considered. Day-to-Day Activities Develop and enhance Python and PySpark data pipelines. Build data marts and optimize transformations and SQL queries. Investigate data quality issues and pipeline failures. Review logs, job results, database records, and performance metrics. Create unit, integration, and data validation tests. Support UAT, deployments, releases, and production incidents. 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, and reliability. Qualifications Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience. Certifications in data engineering, cloud, database, or big-data technologies are preferred. Complete Synechron training on security, data protection, SDLC, and operational procedures. Maintain current knowledge of Python, Spark, data architecture, cloud platforms, data quality, and engineering practices. Professional Competencies Structured problem-solving and data investigation. Ability to analyze complex data issues and identify root causes. Clear communication with technical and business stakeholders. Effective collaboration across development, QA, product, and operations teams. Ability to prioritize development, support, and production issues. Commitment to quality, documentation, testing, and maintainable code. Willingness to learn new data technologies and improve existing processes. SYNECHRON’S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. Candidate Application Notice 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 FinLabs 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 14,500+, and has 58 offices in 21 countries within key global markets. For more information on the company, please visit our website or LinkedIn community. At Synechron, we are committed to integrating sustainability into our business strategy, ensuring responsible growth while minimizing environmental impact. Employees play a key role in driving our sustainability initiatives, from reducing our carbon footprint to fostering ethical and sustainable business practices across global operations. All positions are required to adhere to our Sustainability and Health Safety standards, demonstrating a commitment to environmental stewardship, workplace safety, and sustainable practices. Not finding the right fit? Let us know you're interested in a future opportunity by clicking Get Started below or create an account by clicking 'Sign In' at the top of the page to set up email alerts as new job postings become available that meet your interest!

Data Engineer (Python/PySpark).

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