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Data Engineer (Python, PySpark, Azure Databricks) | Cloud Data Pipelines, Migration & Governance

30+ days ago 2026/09/11
Other Business Support Services
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Job description

Job Summary
Synechron is seeking a skilled Data Engineer with expertise in cloud platforms, large-scale data pipelines, and data security to support our enterprise analytics and data migration initiatives. This role involves designing, developing, and managing scalable data solutions leveraging Python, PySpark, and Azure Databricks. The successful candidate will enable data-driven decision-making, ensure compliance with industry standards, and contribute to our digital transformation roadmap across regulated industries.


Software Requirements
 


Required Software Proficiency:


  • Python (version 3.7 or higher) — extensive hands-on experience in developing automation scripts and data processing solutions


  • PySpark — demonstrated ability in processing large data volumes on Spark clusters


  • Azure Databricks — expertise in developing and managing data pipelines within the Databricks environment


  • SQL — strong query writing, data validation, and performance tuning capabilities in databases like SQL Server, PostgreSQL, or Oracle


  • Azure Data Factory — experience in orchestrating and automating data workflows via Azure services


  • ADLS Gen2 — familiarity with large-scale data storage solutions supporting analytics projects


  • Azure Synapse — understanding of data warehousing and integration in Azure ecosystem


  • Azure Key Vault — knowledge of securing sensitive data and managing secrets


Preferred Software Skills:


  • Databricks Workflows — experience in creating automated, scheduled data workflows in Databricks


  • REST APIs — skills in integrating external data sources and services via API calls


  • Unity Catalog — familiarity with data cataloging, data governance, and metadata management in Databricks


  • Docker — experience in containerizing data pipelines for deployment and scalability


  • Power BI / Tableau — basic experience in creating dashboards and visualizing data insights


Overall Responsibilities


  • Design, develop, and optimize scalable ETL/ELT data pipelines supporting enterprise analytics, migration, and compliance goals


  • Build scalable and resilient data architectures within cloud environments using Azure Data Lake, Databricks, and Synapse Analytics


  • Collaborate closely with data scientists, business analysts, and application teams to translate data requirements into technical solutions


  • Conduct data validation, reconciliation, and security assessments to uphold data governance and compliance standards like GDPR and HIPAA


  • Lead data migration efforts, supporting infrastructure upgrades and cloud adoption initiatives


  • Implement and maintain data security policies, encryption standards, and access controls across platforms


  • Monitor pipeline performance, troubleshoot issues, and optimize resource utilization for cost-effective scalability


  • Automate workflows and infrastructure provisioning using Terraform, Azure DevOps, or similar tools


  • Document data architecture, data lineage, and operational procedures for ongoing support and compliance audits


Technical Skills (By Category)


  • Languages & Data Tools (Essential):


    • Python (3.7+) — scripting and automation for data processing


    • PySpark — large-scale data processing in Spark environments


    • SQL — query development, performance optimization, and validation


  • Databases & Data Management:


    • Relational: SQL Server, PostgreSQL, Oracle


    • Data lakes: Azure Data Lake Storage Gen2


    • Data warehousing: Azure Synapse Analytics


  • Cloud & Infrastructure:


    • Azure Data Factory, Databricks, Synapse, ADLS Gen2 — primary cloud data platform stack


    • Optional: Azure DevOps, Terraform for automation and provisioning


  • Frameworks & Libraries:


    • PySpark, Delta Lake, Dataflow integration in Databricks


  • Security & Governance:


    • Data encryption, role-based access control, GDPR/HIPAA compliance practices


Experience Requirements


  • 6+ years in supporting large-scale, cloud-based data pipelines and architectures


  • Proven ability to design and optimize ETL/ELT workflows supporting business, compliance, and migration needs


  • Demonstrated expertise in data security, privacy policies, and governance in regulated industries


  • Experience with cloud migration projects, integrating multiple data sources, and automating processes


  • Strong troubleshooting skills and ability to improve performance and reliability of data systems


Day-to-Day Activities


  • Develop, test, and optimize data pipelines supporting analytics, reporting, and migration


  • Engage with business and technical teams to translate requirements into scalable data architecture


  • Monitor system performance, troubleshoot failures, and implement performance improvements


  • Conduct data validation, security assessments, and compliance checks aligned with industry regulations


  • Automate workflows and infrastructure setup using Terraform and Azure DevOps pipelines


  • Document data processes, architecture, security policies, and procedures


  • Support ongoing data migration and cloud infrastructure upgrades


  • Collaborate regularly with data scientists, analysts, and platform teams for continuous improvement


Qualifications


  • Bachelor’s or Master’s degree in Data Engineering, Computer Science, or related fields


  • 6+ years supporting enterprise data environments with cloud-native tools and big data frameworks


  • Relevant certifications such as Azure Data Engineer or GCP Professional Data Engineer are a plus


  • Experience supporting secure, compliant, and high-performance data platforms in regulated environments


Professional Competencies


  • Strong analytical and troubleshooting skills for complex data workflows


  • Leadership qualities for guiding junior team members and supporting best practices


  • Effective communication skills for stakeholder engagement and cross-team collaboration


  • Adaptability to evolving cloud technologies and industry standards


  • Innovative mindset with a focus on automation, data quality, and operational security


  • Time management and organizational skills to prioritize tasks effectively in dynamic environments


S​YNECHRON’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.


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