Job DescriptionAbout 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. - Robust 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. - Strong 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 e

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