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.
• 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 engines such as ClickHouse, Dremio, Trino, or Presto.
• Strong understanding of Parquet, ORC, and Avro data formats.
• Experience with object storage systems like S3, ADLS, GCS, or Nutanix Object Storage.
• Strong programming skills in Python / PySpark / Scala.
• Experience with Airflow, Kestra, or similar orchestration tools.
• Hands-on exposure to AWS, Azure, or GCP cloud platforms.
• Experience in telecom data systems or CDR processing is highly preferred. Why join us?
• Impactful Work: Build large-scale data platforms and analytics systems that power real-time communication products used by millions globally.
• Tremendous Growth Opportunities: Accelerate your career by solving complex engineering challenges in a fast-growing CPaaS and product-driven environment.
• Innovative Workplace: Work alongside world-class engineers building cutting-edge distributed data systems, lakehouse architectures, and cloud-native platforms. Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.
Karix.com

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