VisionPlus CMS Tester | API Testing & Test Automation

Job Summary
Synechron is seeking an experienced Data Engineer to design build and optimize data pipelines using Python SQL and Apache Spark. This role focuses on extracting transforming and loading large-scale data sets to support analytics reporting and data-driven decision making. The ideal candidate combines strong technical capabilities with a collaborative mindset contributing to scalable data architectures and efficient data workflows within an agile environment.

Software Requirements

Required Skills (Essential)

• Proficiency in Python for data processing and pipeline development (Pandas/NumPy)

• Strong experience with Apache Spark (PySpark) Spark SQL and Spark-based data transformations

• Advanced SQL skills (query writing data modeling optimization) across relational databases (e.g. MySQL PostgreSQL Oracle)

• Experience designing and building robust data pipelines and ETL processes

• Familiarity with data modeling concepts (star/snowflake schemas) and data warehousing fundamentals

• Experience with version control systems (Git) and collaboration tools (GitHub or GitLab)

• Knowledge of SDLC/Agile methodologies and working in cross-functional teams

• Exposure to data governance data quality and data security considerations

Preferred Skills

• Experience with NoSQL databases (e.g. MongoDB Cassandra) or data lake technologies

• Familiarity with cloud data services (AWS Azure or Google Cloud) and cloud-based data pipelines

• Experience with workflow orchestration tools (e.g. Apache Airflow)

• Knowledge of streaming data frameworks (Kafka Spark Streaming) and real-time processing

• Basic data visualization or reporting experience to support stakeholder storytelling

Overall Responsibilities

• Design develop and maintain end-to-end data pipelines for large-scale enterprise data

• Build and optimize data models and ETL/ELT processes to ensure data quality and performance

• Collaborate with analytics data science and business teams to translate requirements into scalable data solutions

• Implement data governance lineage and security controls across data platforms

• Participate in design reviews code reviews and documentation to ensure maintainability

• Stay current with industry best practices in data engineering Spark and cloud data services

• Promote reusable data components and contribute to continuous process improvement

Technical Skills (By Category)

Programming Languages (Essential)

• Python (advanced for data processing and pipeline development)

• SQL (advanced for data validation and data modeling)

Databases/Data Management

• Relational databases: MySQL PostgreSQL Oracle (data modeling query optimization)

• NoSQL/data lake concepts (preferred)

Cloud Technologies

• Knowledge of cloud data services and architecture (preferred)

• Experience with cloud-based data pipelines (AWS Azure or GCP) (preferred)

Frameworks and Libraries

• Apache Spark (PySpark) Spark SQL Spark Streaming (essential)

• Pandas NumPy (essential)

• Data modeling frameworks and analytics libraries as relevant (preferred)

Development Tools and Methodologies

• Git (version control) GitHub/GitLab

• ETL/ELT tools familiarity (e.g. custom Python pipelines Spark-based ETL)

• Agile/Scrum practices; collaboration with data analytics and BI teams

• Airflow or similar workflow orchestration (preferred)

Security Protocols

• Data privacy data security and data governance best practices (essential)

Experience Requirements

• 49 years in data engineering or a closely related field

• Demonstrated experience building and optimizing data pipelines using Python and Spark

• Experience working with cross-functional teams and delivering data solutions in an enterprise environment

• Preference for domain experience in finance banking or other data-driven industries

• Alternative pathways: strong portfolio of data engineering projects relevant certifications or notable contributions to large-scale data platforms

Day-to-Day Activities

• Develop and maintain scalable data pipelines and ELT processes

• Collaborate with stakeholders to define data requirements and transformation logic

• Design and optimize data models for analytics and reporting

• Validate data quality lineage and governance controls

• Implement and monitor data workflows including scheduling and dependency management

• Perform code reviews and contribute to best practices in data engineering

• Stay current with new data technologies and cloud services; share knowledge with the team

Qualifications

• Bachelors or Masters degree in Computer Science Information Technology Data Science or related field

• Relevant certifications in data engineering cloud platforms or analytics are a plus

Professional Competencies

• Critical thinking and strong analytical problem-solving abilities

• Clear and effective communication with the ability to convey technical concepts to non-technical stakeholders

• Collaboration and teamwork to work effectively with cross-functional teams

• Adaptability to evolving data technologies and business requirements

• Initiative and ownership in delivering high-quality data solutions

• Time management and prioritization in a dynamic environment

SYNECHRONS 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 applicants gender gender identity sexual orientation race ethnicity disabled or veteran status or any other characteristic protected by law.

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