Data Engineer

Actively Reviewing

Techdome

Hyderabad Full-Time 1–2 yrs exp Posted 8 hours ago · Apply by Sep 14, 2026

Job Description

About The Role

We're looking for an early-career Data Engineer to help build and maintain the cloud data platforms that power analytics, BI, and AI/ML for our clients. You'll work alongside senior engineers and consultants to move raw, fragmented data into clean, reliable, query-ready form on Snowflake — supporting everything from customer-360 dashboards to real-time decision-making.

Key Responsibilities

Build, test, and maintain ELT/ETL pipelines using Matillion and Fivetran to ingest data from databases, APIs, files, and SaaS sources into Snowflake.
Develop and maintain SSIS ETL packages and jobs for data integration and scheduled workloads.
Develop and optimize data models and SQL transformations in Snowflake for analytics and reporting use cases.
Work with AWS, including managing data in S3 (staging, ingestion, and storage).
Write clean, reusable Python for data processing, automation, and pipeline logic.
Support data quality, validation, and monitoring so downstream BI (Power BI/Tableau) and ML teams can trust the data.
Track and manage work through Jira workflows; partner with analysts and client stakeholders to translate business questions into data requirements.
Document pipelines, data definitions, and processes.

Must-Have Skills

1–3 years of hands-on experience in data engineering, BI engineering, or a closely related role.
Strong SQL and solid working knowledge of Python.
Hands-on experience with Snowflake.
Experience building pipelines with Matillion and/or Fivetran (ELT), and developing SSIS packages and jobs (ETL).
Working knowledge of AWS, including S3.
Understanding of data warehousing concepts, ETL/ELT, and dimensional modeling.
Familiarity with version control (Git) and Jira workflows.

Good to Have

Experience integrating Salesforce data via Fivetran.
Exposure to Databricks, Redshift, or Synapse.
Experience with BI tools (Power BI, Tableau).
Exposure to data for AI/ML workflows.

What We Look For

Curiosity, ownership, and a problem-solving mindset; comfort working in a consulting/client-delivery environment; clear communication and a willingness to learn fast.