Senior Data Engineer

Senior Data Engineer

Overall Responsibilities

• Design, develop, and maintain scalable data pipelines and architectures to support analytical and operational needs
• Implement data integration solutions, ensuring high data quality, security, and compliance standards
• Collaborate with data scientists, analysts, and engineering teams to translate business requirements into technical solutions
• Optimize data workflows for performance, reliability, and cost-efficiency in cloud environments
• Develop and enforce best practices for data governance, security, and privacy
• Lead efforts in automating data processes and providing documentation for data systems
• Monitor data system performance, troubleshoot issues, and implement improvements
• Contribute to strategic planning around data infrastructure and technology adoption

Software Requirements

• Required:
  • SQL databases (e.g., Microsoft SQL Server, Oracle, PostgreSQL)
  • Big Data tools (e.g., Apache Hadoop, Spark)
  • Cloud platforms (e.g., AWS, Azure, GCP) with experience in data services (e.g., AWS Glue, Google Dataflow)
  • ETL/ELT tools (e.g., Apache NiFi, Talend, Informatica)
• Preferred:
  • Data modeling and visualization tools (e.g., Tableau, Power BI)
  • Containerization and orchestration tools (e.g., Docker, Kubernetes)

Technical Skills

• Programming Languages:
  • Required: Python, SQL (e.g., T-SQL, PL/SQL)
  • Preferred: Scala, Java
• Databases/Data Management:
  • Required: Relational databases, data warehousing solutions
  • Preferred: NoSQL databases (e.g., MongoDB, Cassandra)
• Cloud Technologies:
  • Required: Hands-on experience with AWS, Azure, or Google Cloud Platform services for data processing and storage
  • Preferred: Cloud architecture design, multi-cloud strategies
• Frameworks and Libraries:
  • Required: Spark (PySpark, Spark SQL)
  • Preferred: Kafka, Hadoop ecosystem components
• Development Tools and Methodologies:
  • Required: Git, CI/CD pipelines, Agile/Scrum practices
  • Preferred: Jenkins, Terraform, Docker, Kubernetes
• Security Protocols:
  • Required: Data encryption, access controls, compliance standards (e.g., GDPR, HIPAA)

Experience Requirements

• A minimum of 6 years in data engineering or related roles
• At least 4 years of experience designing and building large-scale data pipelines and systems
• Proven experience working within cloud-based data architectures
• Hands-on project leadership in data integrations, migrations, or large data initiatives
• Experience in dynamic, fast-paced environments with evolving data needs
• Knowledge of industry best practices in data security and compliance

Day-to-Day Activities

• Develop, test, and deploy data pipelines managing structured and unstructured data sources
• Collaborate in daily stand-ups, planning sessions, and cross-team meetings to align project goals
• Monitor system performance, troubleshoot issues, and implement improvement strategies
• Automate routine data processes while ensuring data quality and security standards
• Document data workflows, architecture designs, and operational procedures
• Engage with stakeholders to gather requirements and translate them into technical solutions
• Review and mentor junior team members, fostering a collaborative knowledge-sharing environment

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, or a related field
• Professional certifications such as AWS Certified Data Analytics, Google Cloud Professional Data Engineer, or similar are preferred
• Demonstrated commitment to continuous professional development through training and industry engagement

Soft Skills

• Strong analytical and problem-solving capabilities with a focus on data integrity and quality
• Effective leadership skills and proven ability to work collaboratively in multidisciplinary teams
• Excellent verbal and written communication skills for technical and non-technical audiences
• Ability to adapt to changing priorities, manage multiple projects, and meet deadlines
• Demonstrates innovative thinking and openness to emerging data technologies
• Prioritizes tasks efficiently, balancing strategic initiatives with operational demands

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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