Sr. Lead Analytical Data Engineer

Key Skills

Apache Cassandra, Apache Hive, Data Analytics, Data Architecture, Data Engineering, Data Modeling, Data science techniques, Data Warehousing, Database, Docker, Effective communication skills, HBase, Kubernetes-K8s, Leadership Skill, Machine learning techniques, MLOps tools, MongoDB, NoSQL, Oracle, PySpark, Python Programming, RDBMS, SQL, Unix Operating system

Job Description

We are a global leader in HR technology, offering the latest AI and machine learning-enhanced payroll, tax, HR, benefits, and much more. We believe our people make all the difference in cultivating an inclusive, down-to-earth culture that welcomes ideas, encourages innovation, and values belonging. ADP has a deep commitment to diversity, equity, and inclusion as a global Best Places to Work, DiversityInc® Top 50 Company, Best CEO and company for women, LGBTQ+, multicultural talent, and more. Learn more about ADP’s commitment on our YouTube channel: http://adp.careers/DEI_Videos

WHAT YOU’LL DO:

Behaviors:

• Support the enhancement of data workstreams. As a seasoned data engineer, you strive to contribute to the growth of the team and your own skills. You actively seek opportunities to share your knowledge and collaborate effectively with your colleagues to maintain a high level of productivity.
• Customer-focused. You align data strategies with business objectives, working closely with key stakeholders in business and analytics functions to help them leverage data for added value. Your role involves facilitating data access for data science and business intelligence applications.
• Effective Communicator. You possess strong communication skills, both written and verbal, enabling you to convey data-related information to various team members and leadership. Your ability to articulate working plans and priorities within the team is a valuable asset.
• Deliver Results. You are proactive and hands-on, addressing potential issues and ensuring that tasks are completed with attention to detail. The end product you and your team produce is of high quality and thoroughly polished.
• Your daily tasks are versatile and can include interactions with the Chief Data Officer, participating in leadership meetings to discuss upcoming initiatives, and assisting your team in overcoming obstacles.
• Continuous Improvement. You are committed to documenting existing analytics and automation processes and suggesting and implementing best practices to enhance efficiency and optimization.
• Problem Solving. You are ready to tackle challenges as they arise and find effective solutions to overcome them.

Responsibilities:

• Strategic Data Solution Development: Support 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 – a data modeler.
• 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 execute project plans within a fast-paced agile development environment.
• Data Engineering Expertise: Create 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: Assist the team in prioritizing Business Needs, Leadership Questions, and Ad Hoc Requests to ensure on-time delivery and alignment with organizational goals.
• Quality Assurance: Take the lead in driving 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 5 years of hands-on experience in the implementation, development, improvement, and support of data-related projects.
• Matrix Organization Experience: Experience working in a matrix organization, where you have a product/pod leadership directing the 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: 5+ years of experience in the Health Insurance industry is preferred.
• Problem-Solving Aptitude: Prove your ability to lead a team in leveraging data, analytics, and business acumen to address intricate business challenges.
• Data Platform Experience: Possess hands-on experience with DataBricks, and technologies such as Hadoop, Spark. Demonstrate expertise in managing data housed in various relational databases.
• Data Pipeline Proficiency: Showcase your 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 a valuable 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.