ADP-posted 30 days ago
Full-time • Mid Level
Hybrid • Miami, FL
5,001-10,000 employees
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

ADP is hiring a Lead Analytical Data Engineer for our HR Outsourcing (HRO) Data and Analytics organization. The Lead Analytical Data Engineer will play a key role in growing our newest chapter of analytics engineering professionals while interacting with cross-functional teams to address complex business requirements. We're seeking a value seeking, self-motivated, and analytical profession who act as a player and coach to multiple workstreams at the same time. The role demands the individual to possess technical skills required to perform the job in an effective manner. The right candidate will be a technical expert, should have the passion for data & analytics and works along with the team they manage. What are we looking for? An analytics and data engineering professional with a passion and track record for designing analytics and delivery methods to increase accuracy of reporting and advanced analytics in an agile environment to unlock transformational growth. Someone with intellectual curiosity who wakes up excited to work with a team towards excellence and partner with leaders to drive business outcomes and deliver analytical solutions. The ideal candidate is business-minded, customer-centric, team-oriented, self-motivated, a strategic thinker and results-driven.

  • Strategic Data Solution Development: Be the primary contributor to the development of data solutions with a strategic outlook, focusing on projects with high returns for 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 skillfully 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.
  • 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 8+ 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.
  • 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 especially 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Healthcare Expertise: 3+ years of experience in the Health Insurance industry is preferred.
  • 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.
  • 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.
  • 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.
  • Have courageous team collaboration.
  • Deliver at epic scale.
  • Be surrounded by curious learners.
  • Act like an owner & doer.
  • Give back to others.
  • Join a company committed to equality and equity.
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