Data Engineer

Overview

Synechron is seeking a Data Engineer to design, develop, and maintain scalable data pipelines and ETL processes that support data-driven decision-making across the organization. This role involves working with both structured and unstructured data, ensuring data quality, security, and performance. The Data Engineer will collaborate with data scientists, analysts, and application teams to deliver reliable data solutions that enable business insights and operational efficiency, contributing to our strategic growth initiatives.

Software Requirements

Required Skills:

• Proficiency in SQL (version 2016+, advanced querying and optimization)
• Strong programming experience in Python (2+ years)
• Knowledge of ETL concepts and data integration best practices
• Experience with scheduling and workflow tools like Apache Airflow (or similar)
• Familiarity with data storage solutions and data processing frameworks
  
  

• Experience with Hadoop ecosystem components: HDFS, Hive
• Knowledge of Kafka for real-time data streaming
• Hands-on experience with Spark, Hive, and orchestration tools
• Exposure to cloud data platforms (AWS, GCP, Azure)
• Working knowledge of NoSQL databases such as MongoDB or Cassandra
  
  

Overall Responsibilities

• Design, build, and optimize data pipelines for ingesting, transforming, and loading large volumes of structured and unstructured data.
• Develop and maintain ETL workflows to ensure data accuracy, consistency, and reliability.
• Utilize SQL and Python to process datasets, implement data transformations, and support data analysis.
• Collaborate with technical and non-technical teams to deliver end-to-end data solutions.
• Deploy, monitor, and troubleshoot data workflows in production environments.
• Ensure data security, governance, and compliance across data pipelines.
• Optimize workflows for efficiency, scalability, and cost management.
• Document data processes, maintain version control, and promote best practices for reproducibility.
  
  

Technical Skills (By Category)

Programming Languages:

• Required: SQL (advanced querying, optimization), Python (2+ years)
• Preferred: Knowledge of other scripting languages like Scala or Java
  
  

• Relational: SQL Server, MySQL, PostgreSQL
• Big Data & NoSQL: Hive, Hadoop HDFS, MongoDB, Cassandra
  
  

• Familiarity with cloud data services on AWS, Azure, or GCP
  
  

• Hadoop ecosystem components: HDFS, Hive (preferred)
• Streaming & Processing: Kafka, Spark
  
  

• Version control: Git
• Workflow orchestration: Airflow
• Containerization and deployment: Docker
  
  

• Basic knowledge of data security practices and data privacy standards
  
  

• 3 to 12 years of experience in data engineering, data pipelines, or ETL development
• Proven track record working with large, complex datasets and big data tools
• Experience in designing and optimizing scalable data workflows
• Industry experience in finance, healthcare, or technology sectors is preferred
• Equivalent practical experience or project-based work accepted
  
  

Day-to-Day Activities

• Analyze data requirements, collaborating with stakeholders to design appropriate pipelines
• Develop, test, and deploy data ingestion and transformation workflows
• Maintain and improve data pipelines to enhance performance and reliability
• Monitor data workflows in production, troubleshoot issues, and implement fixes
• Collaborate with data science and analysis teams to support their data needs
• Document workflows, processes, and data schemas
• Participate in team meetings, sprint planning, and code reviews
• Stay updated with emerging data engineering tools and best practices
• Ensure data security, privacy, and compliance protocols are followed
  
  

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field; Master’s degree preferred
• Strong understanding of data modeling, database management, and ETL processes
• Industry certifications in cloud platforms or data engineering are a plus
• Demonstrated ability to work with large data volumes and complex data architectures
  
  

Professional Competencies

• Analytical and problem-solving skills with attention to detail
• Effective communicator able to translate technical concepts for diverse audiences
• Collaborative team player with strong organizational skills
• Self-motivated learner, open to continuous professional development
• Results-oriented with a focus on delivering high-quality, scalable solutions
• Ability to adapt to changing project requirements and adopt new tools and technologies
  
  

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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