Senior Data Engineer - Strategic Analytics & Leadership

WHAT YOU'LL DO:

Behaviors: Lead workstreams that thrive. As an experienced leader, you want everyone to shine. You are constantly looking for ways to share your knowledge, motivate others, and keep everyone engaged and productive. Customer focused. You marry data strategy to business strategy. A trusted partner to key stakeholders across business and analytics functions who understands how data can be activated to deliver value. Your teams are responsible for democratizing data for data science and advanced applications. Clear Communicator. Ability to tell data stories to senior leaders and communicate working plans to the team. Excellent communication skills, both verbal and written; able to communicate effectively with multiple leadership layers and across a broad base of team members. Effective at increasingly complex stakeholder alignment, where priorities often compete, drives transparency on priorities and expected return. Create Results. You’re proactive and hands-on when needed. When you see a potential issue, you never leave things hanging and unfinished. When you and your team deliver a finished product, it’s as polished as you could make it. Variety of work. There is no typical day. You could be checking in with the CDO one minute, meeting with leadership to review initiatives for the coming quarter later and tomorrow helping your team overcome blockers. Influence and inspire confidence. You are comfortable presenting to senior leaders, analytics and program management leads, and peers with a compelling voice that you demonstrate through executive presence, leading change, and creating clear executive-level communications on milestone achievements. Continuous improvement. Document current analytics and automation processes and recommend and implement best practices to improve and optimize. Inevitable challenges will arise, and we’ll rely on you to look for a solution. Responsibilities: Strategic Data Solution Development: Be the primary contributor to the development of data solutions with a strategic outlook, focusing on the broader scope of building and enhancing domains within the semantic layer of HRO. Documentation and Best Practices: Catalog existing analytics and automation processes, and provide recommendations for best practice methods to optimize and improve these processes. Collaborative Stakeholder Engagement: Collaborate closely with Strategic Pod Operations, Data Science, Business Intelligence, and Senior Leadership to create comprehensive roadmaps and execute project plans within a fast-paced agile development environment. Data Engineering Expertise: Lead and create the development of data tables tailored to specific use-cases by skilfully engineering critical elements from multiple data domains. Ensure the ingestion of HRO-specific data is well-structured, compliant with data quality standards, and traceable from the consumption layer back to the raw data layer. Strategic Integration and Security: Partner with the Data Operations, Data Governance and Strategic Pod Operations teams to streamline data integration, maintain data security, and access best practices. Contribute to the creation of end-to-end data analytics solutions. Technological Advancement: Conduct thorough research to identify and recommend cutting-edge technologies and processes that support rapid scaling and future growth initiatives. Prioritization and Delivery: Spearhead the prioritization of Business Needs, Leadership Questions, and Ad Hoc Requests to ensure on-time delivery and alignment with organizational goals. Quality Assurance: Drive the quality assurance and data quality efforts to enhance development timelines, reduce bugs, and maintain the reliability of our analytics products. Iterative Development: Bring your experience in developing v0.5 solutions, incorporating real-world feedback, and iterating to v1.0+ with a continuous improvement mindset. Exceptional Delivery: Leverage your successful track record of superior delivery and change management within an enterprise organization to drive positive change and growth. To succeed in this role: Educational Background: Possess a bachelor’s degree in computer science, engineering, business, statistics, or related fields; advanced degrees are preferred but not mandatory. Experience: Demonstrate a strong foundation in data analytics, engineering, and project management with a minimum of 12 years of hands-on experience in the implementation, development, improvement, and support of data-related projects. Matrix Organization Experience: Showcase 3+ year of experience working in a matrix organization, where you directed the development team to achieve use case goals. Data Expertise: Exhibit deep experience with ETL (Extract, Transform, Load), Data Modeling, and Data Architecture, highlighting your ability to design and maintain data solutions. Industry Knowledge: Preference will be given to candidates with a background in PEO, Service, or Risk analytics, data engineering, data analytics and visualization, business intelligence, or analytical consulting. Problem-Solving Aptitude: Prove your ability to lead a team in leveraging data, analytics, and business acumen to address intricate business challenges. Data Warehouse and Big Data Experience: Possess hands-on experience in designing and maintaining data warehouses and/or data lakes using big data technologies such as Hadoop, Spark, and specially DataBricks. Demonstrate expertise in managing data housed in various relational databases. Data Pipeline Proficiency: Showcase your expert competence in building data pipelines and deploying/maintaining them using tools like Git and Jenkins. MLOps and Containerization Knowledge: Familiarity with MLOps infrastructure (e.g., Databricks, MLflow) and containerization, including experience in managing production pipelines and microservices using technologies like Docker and Kubernetes. Data Analytics Skills: Demonstrate experience and expertise in data mining methods, data modeling, and working with data warehouses, showcasing your ability to extract valuable insights. Technical Skills: Exhibit mastery in Pyspark and SQL, as well as an understanding of agile methodologies and the key factors that contribute to a team's success Preferred Qualifications Proficiency in DataBricks: Hands-on experience and strong technical knowledge with DataBricks, particularly focusing on Apache Spark fundamentals, including Spark Architecture, its API's, and how to leverage it for data processing and analysis. Proficiency in Pyspark/Python/SQL is essential for data manipulation, analysis, and transformation. AWS Certification: AWS certification is highly desirable, reflecting your expertise in cloud technologies and services. Framework Development: Experience in developing frameworks and utility services, including logging/monitoring is an asset, demonstrating your ability to create efficient and scalable solutions. Programming Skills: Proficiency in UNIX and the Python programming language is essential, as it is fundamental for data engineering tasks. Software Development Best Practices: Proven experience in delivering high-quality software following continuous delivery practices and using code quality tools such as JIRA, GitHub, and Jenkins is a strong advantage. Data Storage Solutions: Comfort with a variety of data storage solutions, including RDBMS (e.g., Oracle), Hive, HBase, Impala, and other options, showcases your versatility in handling different data storage needs. NoSQL Databases: Knowledge of NoSQL databases like MongoDB, HBase, Cassandra, etc., is a plus, highlighting your familiarity with a range of data storage technologies. Project Management Tools: Familiarity with Jira and Confluence is preferred, as it facilitates effective project management and documentation. Data Solutions Architecture: While not mandatory, experience as a data solutions architect is considered a significant advantage, demonstrating your ability to design comprehensive data solutions. Cloud Database Technologies: Experience with cloud database technologies, especially in the AWS environment, and the ability to develop solutions on cloud computing services and infrastructure in the data and analytics space is a valuable skill set. PySpark Expertise: Comfort with using PySpark APIs to perform advanced data transformations is a key technical requirement.

YOU'LL LOVE WORKING HERE BECAUSE YOU CAN:

Have courageous team collaboration. Courage comes from how associates are willing to have difficult conversations, speak up, be an owner, and challenge one another's ideas to net out the best solution. Deliver at epic scale. We deliver real user outcomes using strong judgment and good instincts. We're obsessed with the art of achieving simplicity with a focus on client happiness and productivity. Be surrounded by curious learners. We align ourselves with other smart people in an environment where we grow and elevate one another to the next level. We encourage our associates to listen, stay agile, and learn from mistakes. Act like an owner & doer. Mission-driven and committed to leading change, you will be encouraged to take on any challenge and solve complex problems. No tasks are beneath or too great for us. We are hands-on and willing to master our craft. Give back to others. Always do the right thing for our clients and our community and humbly give back to the community where we live and work. Support our associates in times of need through ADP's Philanthropic Foundation. Join a company committed to equality and equity. Our goal is to impact lasting change through our actions. #J-18808-Ljbffr Automatic Data Processing, Inc.