Role Overview The ideal candidate will design, build, and optimize large-scale data pipelines and warehouses that enable real-time analytics and business intelligence across Tanlas CPaaS ecosystem. Youll 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.
- Ensure data quality, integrity,
and governance across distributed systems.
Required Skills:
- 5-7 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 frameworks Hadoop, Spark, Kafka.
- Expertise in data modelling & warehouse design (Star/Snowflake schemas).
- Solid background in CDR parsing and transformation.
- Proficiency in Python/Scala/Java for data workflows.
- Familiarity with cloud platforms such as AWS, GCP, or Azure.
Preferred Qualifications:
- Bachelors or masters degree in computer science, Information Systems, or a related field.
- Experience with Airflow, Snowflake, or Redshift.
- Exposure to telecom data systems or network analytics is highly preferred
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