About the Role:
We are looking for a highly skilled Data Engineer with strong experience in building scalable ETL/ELT pipelines, distributed data systems, and modern lakehouse architectures. The ideal candidate will work on large-scale telecom and CPaaS datasets, including Call Detail Records (CDR), enabling real-time analytics and business intelligence across the platform ecosystem.

What you’ll be Responsible for?
Design and implement scalable ETL/ELT pipelines for large-scale analytics, data processing, and migration workloads.
Build modern data lakehouse platforms using Iceberg, Delta Lake, or Hudi with catalog services like Nessie, AWS Glue, or Hive Metastore.
Develop and optimize high-performance SQL queries and distributed data processing jobs using Spark (PySpark), Hadoop, and Kafka.
Design and manage data warehouses and analytical platforms using Snowflake, ClickHouse, Dremio, Redshift, Trino, or Presto.
Build ingestion and transformation pipelines using object storage systems such as Amazon S3, Azure Data Lake, GCS, or Nutanix Object Storage.




Process and transform telecom datasets and Call Detail Records (CDR) efficiently at scale.
Implement orchestration workflows using Airflow, Kestra, or similar workflow engines.
Ensure data quality, governance, lineage, observability, scalability, and cost optimization across distributed systems.
Build reusable frameworks for bulk data movement, ingestion acceleration, and transformation at scale.

What you’d have?
7 –10 years of experience in Data Engineering or related roles.
Strong expertise in Advanced SQL including query optimization, partitioning, indexing, and performance tuning.
Hands-on experience with Apache Spark (PySpark), Hadoop, Kafka, and distributed data processing systems.
Solid expertise in lakehouse technologies such as Iceberg, Delta Lake, or Hudi.
Experience with metadata/catalog systems including Nessie, Glue, or Hive Metastore.
Knowledge of analytical engines such as ClickHouse, Dremio, Trino, o

📌 Senior Data Engineer (Hyderabad)
🏢 Tanla Platforms
📍 Hyderabad