Data Engineer

Role Overview:

Tanla is seeking a highly skilled Data Engineer with 5-10 years of experience to join our dynamic Data Engineering team in Hyderabad. The ideal candidate will design, build, and optimize large-scale data pipelines and data warehouses that power real-time analytics and business intelligence across Tanlas CPaaS ecosystem. You’ll work on diverse datasets, including Call Detail Records (CDR), and collaborate closely with cross-functional teams to ensure data reliability, scalability, and performance.

Key Responsibilities:

Design and implement ETL/ELT pipelines for large-scale data processing and analytics.

Develop and optimize analytical SQL queries for performance and scalability.

Work with Big Data frameworks such as Hadoop, Spark, and Kafka.

Design, build, and maintain data warehouses and data models supporting reporting and analytics.

Parse and transform Call Detail Records (CDR) and other telecom-related data efficiently.

Collaborate with data scientists, analysts, and business stakeholders to ensure smooth data flow and availability.

Ensure data quality, integrity, and governance across distributed systems.

Required Skills:

5–10 years of hands-on experience in data engineering or a related role.

Strong expertise in Advanced SQL (analytical queries, performance tuning).

Proven experience in ETL/ELT design and data pipeline development.

Hands-on experience with Big Data technologies — Hadoop, Spark, Kafka.

Proficiency in data modeling & warehouse design (Star/Snowflake schemas).

Strong background in CDR parsing and transformation.

Proficiency in Python, Scala, or Java for data workflows.

Familiarity with cloud platforms such as AWS, GCP, or Azure.

Preferred Qualifications:

Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.

Experience with Airflow, Snowflake, or Amazon Redshift.

Exposure to telecom data systems or network analytics is highly preferred