ETL & Data Engineer

Company: GTS TechLabs

Job Title: ETL & Data Engineer

Location: Bangalore

Employment Type: Full-time

Education: B.Tech / M.Tech / MCA

Experience: 45 years (relevant experience required)

Job Summary

We are seeking a skilled and detail-oriented ETL & Data Engineer to design, develop, and optimize scalable data pipelines supporting both real-time and batch processing use cases. The role is critical to enabling advanced analytics in domains such as telecom traffic analysis and fraud detection, with a strong emphasis on performance, reliability, and data security.

Key Responsibilities

Design, develop, and maintain robust ETL workflows for processing high-volume SMS and telecom data.

Build and manage scalable real-time and batch data pipelines using technologies such as Apache Kafka, Spark, Flink, and Hadoop.

Optimize SQL and NoSQL databases for high-performance data storage and retrieval.

Implement data security controls including encryption, masking, and access governance to ensure compliance.

Automate data ingestion, transformation, and orchestration using Python, Apache Airflow, or shell scripting.

Collaborate with cross-functional teams to ensure data quality, consistency, and availability across systems.

Required Skills & Competencies

Hands-on experience with ETL tools and orchestration frameworks such as Python, Apache NiFi, Airflow, Talend, AWS Glue, or equivalent.

Strong expertise in SQL query optimization and database performance tuning.

Solid understanding of OLTP and OLAP systems, including data warehousing and data lake architectures.

Experience with big data and streaming technologies such as Kafka, Spark, Flink, Hadoop, or similar platforms.

Proficiency in relational and NoSQL databases including MySQL, PostgreSQL, MongoDB, Cassandra, and Redis.

Programming proficiency in Python, SQL, and at least one of Scala or Java.

Preferred Qualifications

Experience with cloud platforms such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.

Exposure to AI/ML-driven data pipelines and real-time fraud detection systems.

Relevant certifications in Data Engineering (e.g., AWS Certified Data Analytics, Google Professional Data Engineer).