Nu10
Website:
nu10.co
Job details:
Job Description
Role: Project Manager - Data Engineering / Technical Project Manager
Engagement Type: Full-Time Employee (FTE)
Location: Work from Office – Indiranagar, Bengaluru
Experience: 5+ Years
Company: Nu10 Technologies
We are looking for a Technical Project Manager with a strong background in Data Engineering to lead end-to-end delivery of enterprise data platform initiatives. The ideal candidate should have prior hands-on experience in Data Engineering and possess deep technical understanding of modern data architectures, large-scale data pipelines, cloud data platforms, Spark-based processing, and Data Lake implementations. The candidate should be capable of driving delivery while also providing technical direction to engineering teams.
Key Responsibilities
- Lead end-to-end delivery of Data Engineering and Data Platform projects from planning through production deployment.
- Work closely with Data Engineers, Data Architects, Business Analysts, QA teams, and stakeholders to define project scope, timelines, and deliverables.
- Review and validate solution architecture for enterprise Data Lake implementations.
- Drive implementation of Medallion Architecture (Bronze, Silver, Gold layers) and ensure best practices are followed.
- Oversee the design and development of scalable batch and real-time data pipelines.
- Review technical designs for ETL/ELT pipelines and ensure performance, scalability, reliability, and maintainability.
- Understand and guide Spark/PySpark-based data processing, partitioning, optimization, caching, and performance tuning.
- Ensure proper orchestration and scheduling of data workflows using tools such as Airflow, Azure Data Factory, or similar orchestration platforms.
- Monitor project risks, technical dependencies, resource planning, and delivery milestones.
- Conduct architecture reviews, sprint planning, backlog grooming, and technical discussions with engineering teams.
- Coordinate cross-functional teams to resolve technical blockers and delivery risks.
- Drive implementation of data quality checks, monitoring, logging, and observability frameworks.
- Ensure governance, security, metadata management, and compliance standards are followed across data platforms.
- Collaborate with DevOps teams for CI/CD, infrastructure automation, and production deployments.
- Communicate project status, risks, dependencies, and technical updates to leadership and business stakeholders.
Mandatory Technical Expertise :-
The candidate should possess strong understanding of:
- Data Lake implementation and modernization
- Medallion Architecture (Bronze, Silver, Gold)
- Data Warehouse concepts and dimensional modeling
- ETL and ELT architectures
- Agile/Scrum Delivery
- Client Interactions/ Stakeholder Management
- Data pipelines
- Apache Spark, PySpark, Python
- SQL optimization and performance tuning
- Data partitioning, repartitioning, bucketing, and file optimization
- Data ingestion from databases, APIs, Kafka, files, and cloud storage
- Data modeling (Star Schema, Snowflake Schema)
- Cloud platforms such as AWS, Azure, or GCP
- Data orchestration using Airflow, Azure Data Factory, Glue Workflows, or equivalent
- Data Lake technologies such as S3, ADLS, or GCS
- Delta Lake, Iceberg, or Hudi concepts
- Data Quality, Data Lineage, and Metadata Management
- Monitoring, logging, and production support
- CI/CD Pipelines
Experience
- 8+ years of overall IT experience.
- Minimum 5+ years managing Data Engineering or Data Platform projects.
- Prior hands-on experience as a Data Engineer or Technical Lead.
- Experience delivering enterprise-scale cloud data platform implementations.
What We Are Looking For
The ideal candidate should not only manage project plans but also be technically capable of:
- Reviewing Data Engineering solution designs.
- Understanding pipeline bottlenecks and Spark optimization.
- Challenging engineering decisions with technical reasoning.
- Estimating delivery effort based on technical complexity.
- Managing risks associated with large-scale Data Engineering implementations.
Click on Apply to know more.