ETL QA

Tekskills; Chennai District; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Tekskills in India is hiring for a Data Warehousing & ETL specialist. You will design and optimize data models, develop ETL/ELT pipelines, and ensure data quality across batch and real-time processes.

You will work with SQL, Python, and cloud data services (AWS/Azure). Familiarity with Hadoop/Spark and NoSQL databases is a plus.

Strong analytical skills and ability to translate business requirements into scalable data solutions are essential.

Qualifications

• Deep understanding of data warehousing concepts.
• Experience with ETL/ELT pipelines and data quality checks.
• Knowledge of batch, real-time, and streaming data integration.

Responsibilities

Skills

Data warehousing

ETL/ELT

Advanced SQL

Window functions

Subqueries

Python scripting

Scala

Java

Data modelling

Data integration

Cloud data services

Hadoop

Spark

NoSQL databases

ETL tools

Data quality checks

Tools

Informatica PowerCenter

Talend

Apache NiFi

AWS Glue

Azure Data Factory

Job description

Data Warehousing & ETL Fundamentals:

• Strong understanding of data warehousing
• Expertise in ETL/ELT processes, including data extraction, transformation, loading, and data quality checks
• Familiarity with data integration methodologies (batch processing, real-time processing, data streaming)

Programming & Scripting:

• Proficiency in SQL (including advanced SQL, window functions, subqueries)
• Expertise in at least one scripting language (Python - Preferred) for data manipulation and automation
• Knowledge of other relevant languages (Scala, Java) is a plus

Data Modelling & Design:

• Ability to analyse business requirements and translate them into effective data models
• Experience with data modelling tools is a plus

Data Integration Tools:

• Proficiency in at least one ETL/ELT tool (e.g., Informatica PowerCenter, Talend, Apache NiFi, AWS Glue, Azure Data Factory)
• Experience with cloud-based data integration services (AWS Glue, Azure Data Factory, Google Cloud Dataflow) is a plus

Cloud Technologies:

• Familiarity with cloud platforms (AWS/Azure) and their data services (e.g., cloud storage, data lakes, data warehouses)

Big Data Technologies:

• Experience with big data technologies (Hadoop, Spark, Hive, HDFS) is a plus
• Familiarity with NoSQL databases (e.g., MongoDB, Cassandra) is a plus