DataOS Data Engineer

Key Skills

Apache Airflow, AWS, Azure, Big Data Technology, Data Architecture, Data Engineering, Data science techniques, Databricks, DataOps, Design, Effective communication skills, Google Cloud Platform (GCP), Jenkins, Jupyter Notebook, SQL

Job Description

DataOS Data Engineer collaborating on cutting edge advances in scalable solutions for data ingestion, manipulation and end to end integration of data building blocks to support business driven data products.

Applies developed subject matter knowledge to solve common and complex business issues within established guidelines and recommends appropriate alternatives. Works on problems of diverse complexity and scope. May act as a team or project coach providing direction to team activities and facilitates information validation and team decision making process. Exercises judgment within generally defined policies and practices to identify and select a solution. Ability to handle most unique situations. May seek advice in order to support complex business issues.

Responsibilities

• Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data product pipelines, repositories or models for structured/unstructured data. Focusing on developing sharable libraries that reduce development time and maintenance,
• Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution.
• Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture.
• Leads a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component.
• Collaborates and communicates with project team regarding project progress and issue resolution. Supports co-development processes and tools to promote common approaches to solve complex problems.
• Represents the data engineering team for all phases of larger and more-complex development projects.
• Provides guidance and mentoring to less experienced staff members. Strong technical Leadership is required.

Knowledge & Skills

• Using data engineering tools, languages (Python is a must. Java Scala is a plus), frameworks to mine, cleanse and explore Large Data Sets.
• Fluent in SQL & Cloud based data systems. Relational data modeling.
• Fluent in complex, distributed and massively parallel cloud systems (AWS, GCP, AZURE).
• Strong analytical and problem-solving skills with ability to represent complex algorithms in software.
• Designing data systems/solutions to manage complex data that are highly scalable and performant.
• Ability to performance tune Spark code.
• Strong understanding of database technologies and management systems.
• Strong understanding of cloud-based systems/services. Differentiate benefits for big data Lake House vs. Warehouse.
• Experience with workflow orchestration tools (Airflow, Jenkins)
• Strong Notebooks environment experience (Jupyter, DataBricks)
• Experience collecting requirements from Partners and choosing the right technologies to meet end to end data flow requirements that are required. (Data size, delivery times: hourly, daily monthly or real-time approaches)
• Database architecture testing methodology, including execution of test plans, debugging, and testing scripts and tools.
• Excellent written and verbal communication skills; mastery in English and local language.
• Ability to effectively communicate product architectures, design proposals and negotiate options at management levels.

Scope & Impact

• Collaborates with peers, junior engineers, data scientists and project team.
• Typically interacts with high-level Individual Contributors, Managers and Program Teams.
• Leads a project requiring data engineering solutions development.

Education & Experience

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Engineering or equivalent.
• Typically 4-6 years’ experience.

About HP

You’re out to reimagine and reinvent what’s possible—in your career as well as the world around you. So are we. We love taking on tough challenges, disrupting the status quo, and creating what’s next. We’re in search of talented people who are inspired by big challenges, driven to learn and grow, and dedicated to making a meaningful difference.

HP is a technology company that operates in more than 170 countries around the world united in creating technology that makes life better for everyone, everywhere.