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Bengaluru - Bellandur (GTP), India
Onsite
Job Summary
Synechron is seeking an experienced Data Engineer to design, build, and optimize data pipelines using Python, SQL, and Apache Spark. This role focuses on extracting, transforming, and loading large-scale data sets to support analytics, reporting, and data-driven decision making. The ideal candidate combines strong technical capabilities with a collaborative mindset, contributing to scalable data architectures and efficient data workflows within an agile environment.
Software Requirements
Required Skills (Essential)
Proficiency in Python for data processing and pipeline development (Pandas/NumPy)
Strong experience with Apache Spark (PySpark), Spark SQL, and Spark-based data transformations
Advanced SQL skills (query writing, data modeling, optimization) across relational databases (e.g., MySQL, PostgreSQL, Oracle)
Experience designing and building robust data pipelines and ETL processes
Familiarity with data modeling concepts (star/snowflake schemas) and data warehousing fundamentals
Experience with version control systems (Git) and collaboration tools (GitHub or GitLab)
Knowledge of SDLC/Agile methodologies and working in cross-functional teams
Exposure to data governance, data quality, and data security considerations
Preferred Skills
Experience with NoSQL databases (e.g., MongoDB, Cassandra) or data lake technologies
Familiarity with cloud data services (AWS, Azure, or Google Cloud) and cloud-based data pipelines
Experience with workflow orchestration tools (e.g., Apache Airflow)
Knowledge of streaming data frameworks (Kafka, Spark Streaming) and real-time processing
Basic data visualization or reporting experience to support stakeholder storytelling
Overall Responsibilities
Design, develop, and maintain end-to-end data pipelines for large-scale enterprise data
Build and optimize data models and ETL/ELT processes to ensure data quality and performance
Collaborate with analytics, data science, and business teams to translate requirements into scalable data solutions
Implement data governance, lineage, and security controls across data platforms
Participate in design reviews, code reviews, and documentation to ensure maintainability
Stay current with industry best practices in data engineering, Spark, and cloud data services
Promote reusable data components and contribute to continuous process improvement
Technical Skills (By Category)
Programming Languages (Essential)
Python (advanced for data processing and pipeline development)
SQL (advanced for data validation and data modeling)
Databases/Data Management
Relational databases: MySQL, PostgreSQL, Oracle (data modeling, query optimization)
NoSQL/data lake concepts (preferred)
Cloud Technologies
Knowledge of cloud data services and architecture (preferred)
Experience with cloud-based data pipelines (AWS, Azure, or GCP) (preferred)
Frameworks and Libraries
Apache Spark (PySpark), Spark SQL, Spark Streaming (essential)
Pandas, NumPy (essential)
Data modeling frameworks and analytics libraries as relevant (preferred)
Development Tools and Methodologies
Git (version control), GitHub/GitLab
ETL/ELT tools familiarity (e.g., custom Python pipelines, Spark-based ETL)
Agile/Scrum practices; collaboration with data, analytics, and BI teams
Airflow or similar workflow orchestration (preferred)
Security Protocols
Data privacy, data security, and data governance best practices (essential)
Experience Requirements
4–9 years in data engineering or a closely related field
Demonstrated experience building and optimizing data pipelines using Python and Spark
Experience working with cross-functional teams and delivering data solutions in an enterprise environment
Preference for domain experience in finance, banking, or other data-driven industries
Alternative pathways: strong portfolio of data engineering projects, relevant certifications, or notable contributions to large-scale data platforms
Day-to-Day Activities
Develop and maintain scalable data pipelines and ELT processes
Collaborate with stakeholders to define data requirements and transformation logic
Design and optimize data models for analytics and reporting
Validate data quality, lineage, and governance controls
Implement and monitor data workflows, including scheduling and dependency management
Perform code reviews and contribute to best practices in data engineering
Stay current with new data technologies and cloud services; share knowledge with the team
Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or related field
Relevant certifications in data engineering, cloud platforms, or analytics are a plus
Professional Competencies
Critical thinking and strong analytical problem-solving abilities
Clear and effective communication, with the ability to convey technical concepts to non-technical stakeholders
Collaboration and teamwork to work effectively with cross-functional teams
Adaptability to evolving data technologies and business requirements
Initiative and ownership in delivering high-quality data solutions
Time management and prioritization in a dynamic environment
SYNECHRON’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.