Job Summary
Synechron is seeking a highly experienced PySpark Developer to lead the development and optimization of large-scale data processing workflows. This role involves designing, building, and maintaining robust data pipelines using PySpark, Hadoop, and related big data technologies to support enterprise analytics, machine learning, and Data Science initiatives. The ideal candidate will drive data engineering best practices, ensure data quality and performance, and collaborate with cross-functional teams to deliver scalable and reliable data solutions aligned with organizational goals.
Software Requirements
Required:
Proficiency in Python, PySpark, and Spark (version 2.4+ or higher) for building scalable data pipelines.
Experience with Hadoop ecosystem components such as Hive, MapReduce, or HDFS.
Familiarity with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB).
Version control skills with Git.
Development, orchestration, and scheduling tools such as Apache Airflow, Jenkins, or GitHub Actions.
Experience with containerization tools like Docker.
Data management and transformation using tools such as Pandas and Dask.
Preferred:
Knowledge of cloud data platforms such as AWS or Azure.
Familiarity with DataOps practices, automation tools, and monitoring dashboards such as Prometheus or Grafana.
Overall Responsibilities
Design, develop, and optimize large-scale data processing pipelines using PySpark and Hadoop technologies.
Build efficient, reliable, and scalable data workflows following best practices for performance and data quality.
Implement data transformations, feature engineering, and validation techniques for data science applications.
Collaborate with data scientists, analysts, and product teams to gather requirements and deliver impactful data solutions.
Conduct performance tuning and troubleshooting to resolve data pipeline issues and inefficiencies.
Automate deployment, testing, and operational activities incorporating CI/CD pipelines.
Maintain detailed documentation of data architectures, workflows, and operational procedures.
Support migration projects and cloud integrations to enhance data scalability and security.
Expected outcomes include high-performance data pipelines capable of managing large volume and velocity, with minimal downtime and high data integrity.
Technical Skills (By Category)
Programming Languages:
Essential: Python, PySpark (2.4+ or higher)
Preferred: Java, Scala (for big data processing and integration)
Databases/Data Management:
Essential: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, similar)
Preferred: Data warehousing solutions (Snowflake, Redshift)
Cloud Technologies:
Preferred: AWS (S3, EMR, Glue), Azure Data Factory, cloud-based data processing
Frameworks & Libraries:
Essential: PySpark, Hadoop ecosystem (Hive, MapReduce), Pandas
Preferred: Dask, TensorFlow or other ML integration tools
Development & Automation Tools:
Essential: Git, Jenkins, CI/CD pipelines, Docker, Kubernetes (preferred)
Preferred: Terraform, CloudFormation, DataOps tools like Airflow
Security & Compliance:
Awareness of data encryption, role-based access, GDPR, HIPAA compliance.
Experience Requirements
Minimum of 7+ years of professional experience building large-scale data pipelines in production environments.
Hands-on expertise with PySpark, Hadoop, Spark, and data workflow orchestration tools.
Proven experience with data ingestion, transformation, and validation processes.
Experience supporting enterprise-scale data initiatives in finance, healthcare, retail, or similar sectors preferred; relevant experience in other industries also acceptable.
Strong troubleshooting, performance tuning, and optimization skills.
Day-to-Day Activities
Develop, test, and maintain scalable data pipelines using PySpark and related big data tools.
Optimize existing workflows and implement new features to improve data throughput and reliability.
Collaborate with data scientists, analysts, and engineers to understand data requirements and deliver effective solutions.
Monitor system performance with dashboards, troubleshoot bottlenecks, and resolve operational issues.
Automate deployment, testing, and data validation steps as part of CI/CD pipelines.
Document architecture, data flow, and operational procedures to support ongoing system maintenance and compliance.
Participate in team meetings, code reviews, and knowledge sharing sessions.
Roles involve technical leadership, problem-solving, and proactive communication to ensure data platform excellence.
Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related fields.
5+ years supporting enterprise-level big data environments, with a focus on PySpark and Hadoop ecosystems.
Certifications such as Cloudera, Hortonworks, or AWS Data Analytics are advantageous.
Proven ability to lead technical projects, troubleshoot complex issues, and optimize performance.
Strong verbal and written communication skills, with the ability to collaborate with diverse teams.
Professional Competencies
Strong analytical and problem-solving mindset focused on data quality, performance, and operational stability.
Leadership qualities to guide junior team members and influence best practices.
Effective communication skills for stakeholder engagement and reporting.
Adaptability to evolving big data technologies, cloud platforms, and business demands.
Ownership and initiative to implement continuous improvements.
Excellent time management and prioritization skills to handle multiple projects efficiently.
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.