Back to Browse Jobs
StarRez
Create a free account
One signup unlocks everything for this job:
- See your personalized profile match score
- See the skills this role is missing for you
- Apply to this job and track your application
- Generate an AI cover letter for this role
Hyderabad · On-site · 7-10 Yrs · Oct 30
2 views
1 open role0 posted in 7d1 in 30d
Hiring: Engineering
Job description
Overview
We're redefining how people connect with opportunity through intelligent, human-centered technology.
Responsibilities
- Lead a team of data engineers, providing technical direction, mentorship, and performance management.
- Design, develop, and maintain scalable data pipelines to collect, process, and store data from multiple sources.
- Architect, build, and optimize Databricks Lakehouse solutions supporting enterprise analytics, reporting, AI/ML, and data products.
- Develop large-scale distributed data processing solutions using Databricks, Apache Spark (PySpark), and Delta Lake.
- Implement and manage Medallion Architecture (Bronze, Silver, and Gold) data layers to improve data quality, governance, and usability.
- Build and optimize data infrastructure to support analytics, reporting, and AI/ML workloads at scale.
- Implement event sourcing and streaming architectures using platforms such as Kafka and AWS Kinesis for real-time data processing.
- Leverage Databricks capabilities such as Auto Loader, Delta Live Tables, Databricks Workflows, Unity Catalog, and MLflow to improve platform efficiency and governance.
- Establish best practices for Databricks workspace administration, cluster management, performance tuning, monitoring, and cost optimization.
- Apply data governance, security principles, and compliance frameworks to ensure data quality and regulatory adherence.
- Collaborate with data scientists, software engineers, analytics teams, and product leaders to deliver scalable and reliable data solutions.
- Drive the adoption of modern data engineering practices, frameworks, and tooling across the organization.
- Troubleshoot and resolve complex data-related issues while maintaining data quality, availability, and integrity.
- Contribute to architectural decisions and technology roadmaps for the organization's data platform.
- Mentor data engineers and provide technical leadership across multiple initiatives and teams.
Qualifications
- Bachelor's degree in computer science, engineering, data science, or a related field (or equivalent professional experience).
- 7+ years of experience building enterprise-scale data pipelines, platforms, and distributed data systems.
- Expert-level experience with Databricks and modern Lakehouse architectures.
- Deep expertise in Apache Spark, preferably PySpark, for large-scale distributed data processing.
- Strong hands-on experience with Delta Lake, Unity Catalog, Databricks Workflows, and enterprise Databricks deployments.
- Proficiency in Python and strong familiarity with Java.
- Advanced SQL skills and experience with relational and non-relational databases such as SQL Server, PostgreSQL, MySQL, and MongoDB.
- Strong expertise with cloud platforms, preferably AWS, including services such as S3, Redshift, IAM, and cloud-native data architectures.
- Experience designing and implementing modern data lakes, data warehouses, and lakehouse solutions.
- Expertise with streaming platforms such as Kafka and AWS Kinesis and event-driven architectures.
- Strong understanding of data modeling, warehousing, schema design, and data lifecycle management.
- Experience with data transformation tools such as dbt and business intelligence platforms such as Looker.
- Experience building and exposing APIs for data consumption and integration.
- Strong understanding of Git, CI/CD pipelines, infrastructure automation, and software engineering best practices.
- Experience implementing enterprise data governance, security, and compliance controls across modern data platforms.
- Experience optimizing Databricks clusters, Spark workloads, storage formats, and platform costs.
- Strong analytical, troubleshooting, and problem-solving skills with a passion for continuous learning and innovation.
- Excellent communication and collaboration skills across technical and non-technical audiences.
- Demonstrated experience mentoring engineers, leading technical projects, and influencing architectural decisions.
Verify Python for this role
Free PRACTICE for Python adds a verified skill signal that can boost how roles like this rank for you — optional, not required to browse or apply.
Sign up — verify Python free →Want match scores and deeper insight? Create a free candidate profile
Job application FAQ
Last updated 3 November 2026
- How do I apply for Principle Data Engineer at StarRez?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. StarRez may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this Principle Data Engineer role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Principle Data Engineer remote or on-site in Hyderabad, Telangana?
- This listing is marked on_site with location Hyderabad, Telangana. Confirm details on the job description before applying.
- What skills matter for this Principle Data Engineer role at StarRez?
- This is a mid-level Principle Data Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.