What are the responsibilities and job description for the Associate Data Engineer – HR Analytics position at BrickRed Systems?
We are seeking an Associate Data Engineer to join the HR Analytics Engineering team. This is an excellent opportunity for an early-career engineer to gain hands-on experience across the complete data engineering lifecycle — from data ingestion and transformation to semantic modeling and Power BI reporting.
The ideal candidate will work closely with Senior and Principal Data Engineers to build scalable, production-grade data solutions using Snowflake, Databricks, Microsoft Fabric, and Power BI. This role offers strong learning and growth opportunities with a clear path toward a full Data Engineer position.
Key Responsibilities
- Develop and maintain data pipelines based on solution designs provided by senior engineers
- Implement ingestion, transformation, and data modeling solutions using Snowflake and Databricks
- Work with medallion architecture (Bronze, Silver, Gold layers) and modern data engineering best practices
- Build semantic layer components in Microsoft Fabric and create Power BI dashboards/reports
- Perform unit testing, data validation, reconciliation, and quality checks
- Participate in CI/CD, Git workflows, code reviews, and DevOps practices
- Support production monitoring, troubleshooting, and KTLO activities
- Create and maintain technical documentation including mappings, lineage, and runbooks
- Collaborate with cross-functional teams across US and India teams
- Continuously build domain knowledge in HR Analytics and enterprise data systems
Required Skills & Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
- 2 years of experience in Data Engineering or Software Engineering
- Strong hands-on experience with:
- SQL
- Python (PySpark / Spark SQL)
- Databricks
- Snowflake
- Experience building pipelines from existing technical designs
- Knowledge of ingestion frameworks, medallion architecture, and data modeling
- Exposure to testing frameworks, DevOps practices, and production support ownership
- Familiarity with Git, CI/CD, and Agile methodologies
- Understanding of ETL/ELT concepts and distributed data processing
- Good communication and problem-solving skills
Preferred Qualifications
- Experience with Microsoft Fabric, OneLake, or Power BI
- Exposure to Delta Lake, Iceberg tables, or modern open table formats
- Knowledge of HR Analytics or Telecom domain
- Familiarity with Workday, ServiceNow HR, or enterprise HR systems
- Exposure to streaming technologies such as Kafka or Spark Structured Streaming
- Azure certifications are a plus
Work Environment
- Hybrid role with 3 days onsite in Frisco, TX
- Collaborative global engineering team across US and India
- Opportunity to work on enterprise-scale data platforms and modern cloud technologies
Mandatory Skills
- SQL & Python (PySpark, Spark SQL) – 2 Years
- Databricks & Snowflake – 2 Years
- Pipeline Development from handed-off designs – 2 Years
- Data Modeling & Medallion Architecture – 2 Years
- Testing, DevOps & KTLO Support – 2 Years
About Brickred Systems
Brickred Systems is a global leader in next-generation technology, consulting, and business process service companies. We enable clients to navigate their digital transformation. Brickred Systems delivers a range of consulting services to our clients across multiple industries around the world. Our practices employ highly skilled and experienced individuals with a client-centric passion for innovation and delivery excellence.
With ISO 27001 and ISO 9001 certification and over a decade of experience in managing the systems and workings of global enterprises, we harness the power of cognitive computing hyper-automation, robotics, cloud, analytics, and emerging technologies to help our clients adapt to the digital world and make them successful. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
Salary : $45 - $50