Data Engineering Manager
Pune, Maharashtra, India
Hewlett Packard Enterprise
Discover HPE edge-to-cloud, enterprise compute IT, data, and security solutions. Learn how HPE empowers digital transformation through AI and sustainability.This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2-3 days per week from an HPE office.
Who We Are:
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
HPE Operations is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you.
What you’ll do:
We are seeking a Data Engineering Manager to lead, manage, and deliver complex data engineering projects. This role requires a strong blend of technical expertise, project management skills, stakeholder collaboration, and leadership. The ideal candidate will ensure the successful delivery of data solutions aligned with business objectives, driving innovation and operational excellence across the organization. Also collaborate with cross-functional teams to understand data requirements and optimize systems for data analytics and machine learning applications.
Key Responsibilities:
Delivery Management: Plan, execute, and manage end-to-end delivery of data engineering projects, ensuring they meet quality, timeline, and budgetary requirements. Implement best practices in Agile, Scrum, or other relevant methodologies for iterative and efficient project delivery. Establish robust mechanisms to monitor project progress, identify risks, and ensure proactive resolution.
Technical Leadership: Provide guidance on the design, development, and deployment of scalable data pipelines, ETL/ELT processes, and data storage solutions. Oversee the integration of cloud-based or on-premises data platforms.
Team Leadership: Build, mentor, and lead a high-performing team of data engineers, fostering a culture of collaboration, innovation, and accountability. Conduct performance reviews, provide feedback, and develop professional growth plans for team members.
Stakeholder Engagement: Act as a primary point of contact for stakeholders, ensuring alignment of technical solutions with business needs. Translate business requirements into technical deliverables and prioritize tasks effectively. Collaborate with cross-functional teams, including product managers, data scientists, and analysts, to deliver cohesive solutions.
Technical Expertise:
- Architect and develop end-to-end data pipelines that efficiently ingest, process, and store structured and unstructured data from diverse sources.
- Leverage batch and real-time processing methods to handle various data flows, ensuring that both historical and streaming data are seamlessly integrated.
- Implement automated data validation and quality checks at each stage of the pipeline to ensure that data is accurate, complete, and consistent.
- Define and implement data transformation rules that standardize, clean, and enrich data to make it usable for analysis and reporting.
- Design efficient ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes that balance processing time with resource utilization.
- Set up monitoring and alerting systems to track the health and performance of data pipelines, ensuring that any failures or performance issues are quickly identified and resolved
- Collaborate with data architects and infrastructure teams to integrate data pipelines with other systems, ensuring seamless data movement across the organization.
- Ensure proper lineage and governance of the data as it flows through the pipeline, making it easier to track, audit, and comply with regulatory requirements.
- Develop comprehensive proofs of concept (POCs) for our core platforms, CDP and EDF, focusing on their ecosystem components. This will provide a solid foundation for most of our projects and accelerate initial setup and configuration.
- Design and implement reusable templates for common data pipeline patterns, covering ingestion, transformation, and loading processes. These templates will serve as starting points for new projects, reducing development time.
What you need to bring:
- The overall experience is between 10-15 years
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- Proficiency in programming languages such as Python or Java.
- Extensive experience working with big data technologies such as Airflow, Hadoop, Spark, Kafka,
- Strong proficiency with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra, Cloudera).
- Experience in on prem data engineering open source tools.
- Strong experience in data modeling, data warehousing, and ETL frameworks.
- Familiarity with data governance practices, data privacy, and security standards.
- Experience with containerization and orchestration tools like Docker and Kubernetes.
- Good to have databricks and Snowflake experience
- Knowledge of CI/CD pipelines, version control systems, and agile methodologies.
- Good to have: Experience in building AI systems using data
Additional Skills:
Accountability, Accountability, Action Planning, Active Learning (Inactive), Active Listening, Bias, Business Growth, Business Planning, Cloud Computing, Cloud Migrations, Coaching, Commercial Acumen, Creativity, Critical Thinking, Cross-Functional Teamwork, Customer Experience Strategy, Data Analysis Management, Data Collection Management (Inactive), Data Controls, Design Thinking, Empathy, Follow-Through, Growth Mindset, Hybrid Clouds, Infrastructure as a Service (IaaS) {+ 10 more}What We Can Offer You:
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Diversity, Inclusion & Belonging
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know diverse backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.
Let's Stay Connected:
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ServicesJob Level:
Manager_1
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT and Affirmative Action employer. We are committed to diversity and building a team that represents a variety of backgrounds, perspectives, and skills. We do not discriminate and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global diverse team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO F/M/Protected Veteran/ Individual with Disabilities.
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Airflow Big Data Cassandra CI/CD Computer Science CX Data analysis Data Analytics Databricks Data governance Data pipelines Data Warehousing Docker ELT Engineering ETL Hadoop Java Kafka Kubernetes Machine Learning MongoDB MySQL NoSQL Open Source Pipelines PostgreSQL Privacy Python Scrum Security Snowflake Spark SQL Streaming Unstructured data
Perks/benefits: Career development Health care Startup environment
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