Senior ETL & Data Streaming Engineer

Actively Reviewing the Applications

DataFlow Group

4–8 years

Posted 3 days ago • Apply by June 11, 2026

Job Description

Role Overview

We are looking for a highly skilled and experienced Senior ETL & Data Streaming Engineer with over 10 years of experience to play a pivotal role in designing, developing, and maintaining our robust data pipelines. The ideal candidate will have deep expertise in both batch ETL processes and real-time data streaming technologies, coupled with extensive hands-on experience with AWS data services. A proven track record of working with Data Lake architectures and traditional Data Warehousing environments is essential.

Key Responsibilities

Design, develop, and implement highly scalable, fault-tolerant, and performant ETL processes using industry-leading ETL tools to extract, transform, and load data from various source systems into our Data Lake and Data Warehouse.
Architect and build batch and real-time data streaming solutions using technologies like Talend, Informatica, Apache Kafka or AWS Kinesis to support immediate data ingestion and processing requirements.
Utilize and optimize a wide array of AWS data services, including but not limited to AWS S3, AWS Glue, AWS Redshift, AWS Lake Formation, AWS EMR, and others, to build and manage data pipelines.
Collaborate with data architects, data scientists, and business stakeholders to understand data requirements and translate them into efficient data pipeline solutions.
Ensure data quality, integrity, and security across all data pipelines and storage solutions.
Monitor, troubleshoot, and optimize existing data pipelines for performance, cost-efficiency, and reliability.
Develop and maintain comprehensive documentation for all ETL and streaming processes, data flows, and architectural designs.
Implement data governance policies and best practices within the Data Lake and Data Warehouse environments.
Mentor junior engineers and contribute to fostering a culture of technical excellence and continuous improvement.
Stay abreast of emerging technologies and industry best practices in data engineering, ETL, and streaming.

Required Qualifications

10+ years of progressive experience in data engineering, with a strong focus on ETL, ELT and data pipeline development.
Deep expertise in ETL Tools : Extensive hands-on experience with commercial or open-source ETL tools (Talend)
Strong proficiency in Data Streaming Technologies : Proven experience with real-time data ingestion and processing using platforms such as AWS Glue,Apache Kafka, AWS Kinesis, or similar.
Extensive AWS Data Services Experience :
Proficiency with AWS S3 for data storage and management.
Hands-on experience with AWS Glue for ETL orchestration and data cataloging.
Strong knowledge of AWS Redshift for data warehousing and analytics.
Familiarity with AWS Lake Formation for building secure data lakes.
Good to have experience with AWS EMR for big data processing .
Data Warehouse (DWH) Knowledge : Strong background in traditional data warehousing concepts, dimensional modeling (Star Schema, Snowflake Schema), and DWH design principles.
Programming Languages : Proficient in SQL and at least one scripting language (e.g., Python, Scala) for data manipulation and automation.
Database Skills : Strong understanding of relational databases and NoSQL databases.
Version Control : Experience with version control systems (e.g., Git).
Problem-Solving : Excellent analytical and problem-solving skills with a keen eye for detail.
Communication : Strong verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.