Big Data Engineer (Java, Spark, Hadoop, NoSQL, Cloud)

Job Summary

Synechron is seeking a motivated and experienced Big Data Engineer to design, develop, and implement scalable big data solutions. The ideal candidate will possess strong hands-on experience with Hadoop, Spark, and NoSQL databases, enabling the organization to ingest, process, and analyze vast data sets efficiently. This role contributes directly to the organization’s data-driven initiatives by creating reliable data pipelines and collaborating with cross-functional teams to deliver insights that support strategic decision-making and operational excellence.

Purpose:
To build and maintain optimized big data architectures that support real-time and batch data processing, enabling analytics, reporting, and machine learning efforts.

Value:
By ensuring high-performance and scalable data platforms, this role accelerates data insights, enhances business agility, and ensures data integrity and security.

Software Requirements

Required Skills:

• Deep expertise in Hadoop ecosystem components including Hadoop Distributed File System (HDFS), Spark (batch and streaming), and related tools.
• Practical experience with NoSQL databases such as Cassandra, MongoDB, and HBase.
• Experience with data ingestion tools like Spark Streaming and Apache Flume.
• Strong programming skills in Java, Scala, or Python.
• Familiarity with DevOps tools such as Git, Jenkins, Docker, and container orchestration with OpenShift or Kubernetes.
• Working knowledge of cloud platforms like AWS and Azure for deploying and managing data solutions.

Preferred Skills:

• Knowledge of additional data ingestion and processing tools.
• Experience with data cataloging or governance frameworks.

Overall Responsibilities

• Design, develop, and optimize large-scale data pipelines and data lakes using Spark, Hadoop, and related tools.
• Implement data ingestion, transformation, and storage solutions to meet business and analytic needs.
• Collaborate with data scientists, analysts, and cross-functional teams to translate requirements into technical architectures.
• Monitor daily data operations, troubleshoot issues, and improve system performance and scalability.
• Automate deployment and maintenance workflows utilizing DevOps practices and tools.
• Ensure data security, privacy, and compliance standards are upheld across all systems.
• Stay updated with emerging big data technologies to incorporate innovative solutions.

Strategic objectives:

• Enable scalable, reliable, and efficient data processing platforms to support analytics and AI initiatives.
• Improve data quality, accessibility, and timeliness for organizational decision-making.
• Drive automation and continuous improvement in data infrastructure.

Performance outcomes:

• High reliability and performance of data pipelines with minimal downtime.
• Increased data ingestion and processing efficiency.
• Strong collaboration across teams leading to successful project outcomes.

Technical Skills (By Category)

Programming Languages:

• Essential: Java, Scala, or Python for developing data pipelines and processing scripts.
• Preferred: Knowledge of additional languages such as R or SQL scripting for data manipulation.

Databases & Data Management:

• Experience with Hadoop HDFS, HBase, Cassandra, MongoDB, and similar NoSQL data stores.
• Familiarity with data modeling, ETL workflows, and data warehousing strategies.

Cloud Technologies:

• Practical experience deploying and managing big data solutions on AWS (e.g., EMR, S3) and Azure.
• Knowledge of cloud security practices and resource management.

Frameworks & Libraries:

• Extensive use of Hadoop, Spark (structured and streaming), and related libraries.
• Familiarity with serialization formats like Parquet, Avro, or ORC.

Development Tools & Methodologies:

• Proficiency with GIT, Jenkins, Docker, and OpenShift/Kubernetes for versioning, CI/CD, and containerization.
• Experience working within Agile/Scrum environments.

Security & Data Governance:

• Comprehension of data security protocols, access controls, and compliance regulations.

Experience Requirements

• 4 to 7 years of hands-on experience in Big Data engineering or related roles.
• Demonstrable experience designing and maintaining large-scale data pipelines, data lakes, and data warehouses.
• Proven aptitude for using Spark, Hadoop, and NoSQL databases effectively in production environments.
• Prior experience in financial services, healthcare, retail, or telecommunications sectors is a plus.
• Ability to lead technical initiatives and collaborate with multidisciplinary teams.

Day-to-Day Activities

• Develop and optimize data ingestion, processing, and storage workflows.
• Collaborate with data scientists and analysts to architect solutions aligned with business needs.
• Build, test, and deploy scalable data pipelines ensuring high performance and reliability.
• Monitor system health, diagnose issues, and implement improvements for data systems.
• Conduct code reviews and knowledge sharing sessions within the team.
• Participate in sprint planning, daily stand-ups, and project reviews to ensure timely delivery.
• Stay current with evolving big data tools and best practices.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
• Relevant certifications in big data technologies or cloud platforms are a plus.
• Demonstrable experience leading end-to-end data pipeline solutions.

Professional Competencies

• Strong analytical, troubleshooting, and problem-solving skills.
• Effective communicator with the ability to explain complex concepts to diverse audiences.
• Ability to work collaboratively in a team-oriented environment.
• Adaptability to emerging technologies and shifting priorities.
• High level of organization and attention to detail.
• Drive for continuous learning and process improvement.

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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