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



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

nWhat you'd have?
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- 7 –10 years of experience in Data Engineering or related roles.n
- Strong expertise in Advanced SQL including query optimization, partitioning, indexing, and performance tuning.n
- Hands-on experience with Apache Spark (PySpark), Hadoop, Kafka, and distributed data processing systems.n
- Strong expertise in lakehouse technologies such as Iceberg, Delta Lake, or Hudi.n
- Experience with metadata/catalog systems including Nessie, Glu

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