NCompas Business Solutions Inc.
Website:
ncompasbusiness.com
Job details:
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
- Professional development and learning opportunities
- Career growth prospects in a fast-growing organization
Click on Apply to know more.
