Description
Staff Data EngineerRole OverviewWe are seeking an experienced Staff Data Engineer to join the NPS Prism engineering team a Bain platform that provides advanced analytics, benchmarking, and insights into customer experience metrics across industries.As a senior technical leader, you will be responsible for designing, building, and optimizing large-scale, high-performance data pipelines and architectures that power NPS Prism s analytics and client-facing applications. This role requires deep Databricks expertise, proficiency in Python, SQL, and PySpark, and the ability to work across cloud-native environments (Azure, AWS, or GCP).You ll collaborate closely with data scientists, product managers, and business stakeholders to shape and execute the platform s data strategy, ensuring data quality, scalability, and reliability at enterprise scale.
Key Responsibilities
- Data Architecture Engineering Leadership
- Design and own scalable data architectures for ingestion, transformation, and analytics on Databricks.
- Build robust ETL/ELT pipelines using PySpark, SQL, and Databricks Workflows.
- Lead performance tuning, partitioning, and data optimization across large distributed systems.
- Mentor junior data engineers and enforce best practices for code quality, testing, and version control.
- Cloud Platform Engineering
- Develop and maintain data lakes and data warehouses on cloud platforms (Azure Data Lake, AWS S3, GCP BigQuery, etc.).
- Utilize Azure Data Factory, AWS Glue, or similar orchestration tools to manage large-scale data workflows.
- Integrate multiple data sources (structured, semi-structured, and unstructured) into unified models for NPS Prism analytics.
- Databricks Advanced Analytics Enablement
- Leverage Databricks for large-scale data processing, Delta Lake management, and ML/AI enablement.
- Drive the adoption of Databricks Unity Catalog, governance, and performance features.
- Partner with analytics teams to enable seamless model training and inference pipelines on Databricks.
- Data Quality, Observability Governance
- Define and implement frameworks for data validation, monitoring, and error handling.
- Collaborate with platform teams to establish data lineage and governance using tools like Great Expectations, Monte Carlo, or Databricks-native observability.
- Ensure compliance with Bain s data security and privacy standards.
- DevOps CI/CD for Data
- Implement CI/CD pipelines for data code deployments using Git, Azure DevOps, or Jenkins.
- Automate testing, deployment, and monitoring for data workflows to ensure reliability and repeatability.
- Cross-Functional Collaboration
- Work with product and business teams to translate analytical requirements into scalable technical designs.
- Collaborate with Data Science and BI teams to deliver analytics-ready datasets for dashboards and models.
- Serve as a technical advisor in architectural reviews and strategic data initiatives within NPS Prism.
Required Skills And Qualifications
Core Technical Expertise:
- Advanced proficiency in Databricks (mandatory).
- Strong command of Python, SQL, and PySpark for big data processing.
- Experience with Delta Lake, Spark optimization, and cluster management.
- Hands-on with ETL/ELT design, data lake and warehouse architecture.
- Cloud expertise in Azure, AWS, or GCP (Azure preferred).
Leadership Architecture
- 6 to 8 years of data engineering experience, with at least 3 years in a lead or staff-level role.
- Proven ability to design end-to-end data solutions and influence engineering best practices.
- Strong mentorship and stakeholder management skills.
Additional Desirable Skills
- Familiarity with streaming frameworks (Kafka, Event Hubs).
- Understanding of data modeling and BI integration (Power BI, Tableau).
- Exposure to DevOps, CI/CD pipelines, and Infrastructure as Code (IaC).
- Strong problem-solving and analytical skills.
Educational Qualifications
- Bachelor s or Master s degree in Computer Science, Information Systems, or a related field.
(ref:hirist.tech)
