About NCompas

NCompas is a human-centric digital technology partner for mid-market & enterprise organizations with a mission to help companies navigate the technology landscape by combining practical advisory, product engineering, and Data, AI expertise into one globally integrated team. We blend startup agility with enterprise grade reliability and we are focused on amplifying human potential with AI and digital solutions, and not constrained by them. We advise, build, and continuously evolve modern digital and AI solutions that accelerate growth, control costs, and deliver lasting business impact.

The Opportunity

We are looking for a Data Engineer with 2-4 years of hands-on experience to build and maintain the data pipelines that power analytics, reporting, and AI-driven solutions for our clients.

This role is ideal for someone who is already strong in SQL and Python, has shipped real pipelines in Azure, and is ready to take full ownership of their work while growing toward a senior role. Role Overview

You will build, test, and maintain data pipelines end-to-end, turning raw data from a range of source systems into clean, reliable datasets that business teams can trust. You will work alongside senior data engineers, analysts, and project managers across client and internal projects, owning the pipelines assigned to you from development through to production support.

Location: Hyderabad, Telangana (Office-based) Key ResponsibilitiesData Pipelines & ETL

Build, test, and maintain data pipelines and ETL/ELT workflows across a range of source systems

Develop and maintain pipelines in Azure Data Factory, including scheduling, monitoring, and troubleshooting failures

Write and optimize SQL queries and Python scripts for data extraction, transformation, and loading

Data Modeling & Warehousing

Build and maintain data models and tables that support reporting and analytics use cases





Apply sound modeling practices including fact and dimension tables, star schema, and normalization

Tune queries and pipelines for performance and cost efficiency

Reporting & Business Intelligence

Create dashboards and reports in Power BI based on business requirements

Prepare clean, well-structured datasets for analysts and data science teams

Ensure reporting layers stay accurate and refresh reliably

Data Quality & Reliability

Apply data quality checks and validation rules to ensure accuracy and completeness of delivered data

Investigate and resolve data issues raised by business stakeholders or downstream consumers

Support data cataloging, documentation, and metadata upkeep for the pipelines you own

Work with senior engineers to implement data governance, access control, and security practices

Collaboration & Delivery

Translate business requirements into working data solutions with guidance from senior team members

Participate in code reviews, agile ceremonies, and team knowledge-sharing sessions

Document pipeline logic, data flows, and operational runbooks

Communicate progress, blockers, and data issues clearly to technical and non-technical colleagues

Required Skills

2-4 years of hands-on experience in data engineering, ETL development, or a related data role

Strong programming skills in Python and SQL

Hands-on experience with Azure Data Factory, including building and maintaining pipelines, data flows, and scheduled runs

Working knowledge of Power BI or a similar data visualization tool





Solid understanding of data modeling and schema design, including fact and dimension tables and star schema

Experience with a cloud data warehouse such as Azure Synapse, Snowflake, Redshift, or BigQuery

Understanding of relational databases and query optimization fundamentals, including indexes, joins, and execution plans

Familiarity with version control using Git

Awareness of data quality and data governance concepts and why they matter in a production pipeline

Strong problem-solving skills, attention to detail, and clear communication

Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field, or equivalent practical experience

Nice to Have

Experience with Databricks, Delta Lake, or Medallion architecture using Bronze, Silver, and Gold layers

Hands-on experience with Apache Spark using PySpark or Spark SQL

Experience with data orchestration tools such as Apache Airflow, Prefect, or Dagster

Exposure to streaming data tools such as Kafka, Spark Streaming, or Azure Event Hubs

Familiarity with CI/CD for data pipelines using Azure DevOps or GitHub Actions, and DataOps practices

Exposure to AI/ML workflows, such as preparing datasets or supporting feature engineering for data science teams

Exposure to Data Fabric concepts including data integration, virtualization, and metadata management

Basic knowledge of Infrastructure as Code using Terraform or ARM templates

Certifications such as DP-203, PL-300, or Azure Data Engineer Associate

What We Offer

Opportunity to work on enterprise-scale data engineering projects

Mentorship from senior data engineers and a clear growth path toward senior roles

Collaborative and innovative work environment

Career development and learning opportunities

Career growth prospects in a fast-growing organization

📌 Data Engineer (Hyderabad)
🏢 NCompas Technology Solutions
📍 Hyderabad