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Data Engineer - Python / SQL

Data Engineer - Python / SQL

KJBN LabsBangalore
9 hours ago
Job description

Description :

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 cost-efficiency.
  • Data Integration : Integrate data from diverse sources, including APIs, third-party 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 data-related 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 : 3+ 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
  • Expertise in SQL and experience with NoSQL databases (e.g., MongoDB, Cassandra).
  • Strong experience with cloud platforms (e.g., AWS, GCP) and their data services (e.g., Redshift, BigQuery, Snowflake).
  • Hands-on 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 problem-solving and analytical skills.
  • Strong communication and collaboration abilities.
  • Ability to work in a fast-paced, 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.
  • (ref : hirist.tech)

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