NA

Highlights:

3.00 - 9.00 Years

25.00 - 36.00 INR (Lacs)/Yearly

Full-time

bangaluru

Roles & Responsibility

Education: Bachelor’s or Master’s 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). 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.

Requirements





Education: Bachelor’s or Master’s 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). Solid experience with cloud platforms (e.g., AWS, Azure, 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.

📌 Senior Data Engineer Na (India)
🏢 Skyleaf Consultants
📍 India