Senior Data Engineer
Senior Data Engineer
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Job Description
Company: KJBN Labs
Location: Bangalore (Hybrid)
Overview
The Senior Data Engineer will design develop and maintain scalable data pipelines and infrastructure to support datadriven decisionmaking and advanced analytics. This role requires deep expertise in data engineering strong problemsolving skills and the ability to collaborate with crossfunctional teams to deliver robust data solutions.
Key Responsibilities
Data Pipeline Development: Design build and optimize scalable secure and reliable data pipelines to ingest process and transform large volumes of structured and unstructured data.
Data Architecture: Architect and maintain data storage solutions including data lakes data warehouses and databases ensuring performance scalability and costefficiency.
Data Integration: Integrate data from diverse sources including APIs thirdparty systems and streaming platforms ensuring data quality and consistency.
Performance Optimization: Monitor and optimize data systems for performance scalability and cost implementing best practices for partitioning indexing and caching.
Collaboration: Work closely with data scientists analysts and software engineers to understand data needs and deliver solutions that enable advanced analytics machine learning and reporting.
Data Governance: Implement data governance policies ensuring compliance with data security privacy regulations (e.g. GDPR CCPA) and internal standards.
Automation: Develop automated processes for data ingestion transformation and validation to improve efficiency and reduce manual intervention.
Mentorship: Guide and mentor junior data engineers fostering a culture of technical excellence and continuous learning.
Troubleshooting: Diagnose and resolve complex datarelated issues ensuring high availability and reliability of data systems.
Required Qualifications
Education: Bachelors or Masters degree in Computer Science Engineering Data Science or a related field.
Experience: 5 years of experience in data engineering or a related role with a proven track record of building scalable data pipelines and infrastructure.
Technical Skills:
Proficiency in programming languages such as Python Java or Scala.
Expertise in SQL and experience with NoSQL databases (e.g. MongoDB Cassandra).
Strong experience with cloud platforms (e.g. AWS Azure GCP) and their data services (e.g. Redshift BigQuery Snowflake).
Handson experience with ETL/ELT tools (e.g. Apache Airflow Talend Informatica) and data integration frameworks.
Familiarity with big data technologies (e.g. Hadoop Spark Kafka) and distributed systems.
Knowledge of containerization and orchestration tools (e.g. Docker Kubernetes) is a plus.
Soft Skills:
Excellent problemsolving and analytical skills.
Strong communication and collaboration abilities.
Ability to work in a fastpaced dynamic environment and manage multiple priorities.
Certifications (optional but preferred): Cloud certifications (e.g. AWS Certified Data Analytics Google Professional Data Engineer) or relevant data engineering certifications.
Preferred Qualifications
Experience with realtime data processing and streaming architectures.
Familiarity with machine learning pipelines and MLOps practices.
Knowledge of data visualization tools (e.g. Tableau Power BI) and their integration with data pipelines.
Experience in industries with high data complexity such as finance healthcare or ecommerce.
Work Environment
Team: Collaborative crossfunctional team environment with data scientists analysts and business stakeholders.
Hours: Fulltime with occasional oncall responsibilities for critical data systems.
Required Experience:
Manager
Employment Type
Full-Time
