Big Data Engineer

We are

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.

Our Challenge
As a Big Data Engineer, candidate will be instrumental in developing and optimizing big data technologies such as Apache Spark and Azure Databricks. Candidate will create robust data pipelines, ensure high data quality, and collaborate closely with cross-functional teams to implement scalable cloud-native solutions on major cloud providers, predominantly Microsoft Azure.

Additional Information*

The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Weehawken, NJ is $130k - $140k/year & benefits (see below).

The Role

Responsibilities:

• Develop, optimize, and maintain big data pipelines using Apache Spark, Azure Databricks, and related tools.
• Write and deploy complex production systems in Scala, Java, or Python, ensuring high performance and reliability.
• Leverage Terraform for automating cloud infrastructure deployment on Azure or other major cloud providers.
• Design and implement CI/CD pipelines for data workflows using modern tools like GitLab, promoting automation and continuous improvement.
• Apply best practices for testing, instrumentation, observability, and alerting to maintain data pipeline health and performance.
• Contribute to system architecture and low-level design, ensuring modularity, scalability, and security.
• Understand and implement data models, data structures, and algorithms for efficient data processing.
• Use containerization technologies such as Docker and Kubernetes for development, build, and runtime environments.
• Work within Agile development teams, participating in planning, daily stand-ups, and iterative releases.
• Collaborate effectively in a global team, influencing key architectural decisions and sharing best practices.

Requirements:

• Proven experience developing big data solutions with Apache Spark and Azure Databricks.
• Hands-on experience with Terraform for infrastructure as code (IaC) on major cloud platforms, ideally Azure.
• Programming expertise in Scala, Java, or Python for complex production systems.
• Extensive Python experience, especially in data engineering contexts.
• Background in platform engineering roles on cloud platforms, with strong knowledge of Azure services.
• Practical knowledge of testing frameworks, instrumentation, observability, and alerting tools.
• Experience building and maintaining CI/CD pipelines with modern cloud-friendly systems like GitLab.
• Deep understanding of information modeling, data structures, and algorithms.
• Hands-on experience with containerization (Docker) and orchestration tools (Kubernetes).
• Strong understanding of technical architecture and low-level system design.
• Familiarity with Agile methodologies and best practices in software development.

Preferred, but not required:

• Experience working with financial or risk management data.
• Knowledge of data governance, security standards, and compliance in cloud environments.
• Familiarity with additional cloud providers and multi-cloud deployment strategies.
• Contributions to open-source data projects or communities.

We offer:

• A highly competitive compensation and benefits package.
• A multinational organization with 58 offices in 21 countries and the possibility to work abroad.
• 10 days of paid annual leave (plus sick leave and national holidays).
• Maternity & paternity leave plans.
• A comprehensive insurance plan including medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region).
• Retirement savings plans.
• A higher education certification policy.
• Commuter benefits (varies by region).
• Extensive training opportunities, focused on skills, substantive knowledge, and personal development.
• On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses.
• Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups.
• Cutting edge projects at the world's leading tier-one banks, financial institutions and insurance firms.
• A flat and approachable organization.
• A truly diverse, fun-loving, and global work culture.

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.