Lead Data Solutions Developer

Position Summary

The Lead Data Engineer – Sales plays a critical role in transforming raw data into actionable insights and enabling analytics across the organization. Operating within a federated business Data and Analytics team, you will help build the commercial data engineering function from the ground up while designing, implementing, and maintaining scalable data pipelines and reporting-layer data objects that support business intelligence, analytics, and data science initiatives.

You will work closely with STERIS Healthcare business stakeholders to understand data requirements and deliver reliable, accessible, and optimized data solutions. As a subject matter expert, you will guide cross-functional partners in leveraging data to drive informed decision-making and contribute to the organization’s overarching data strategy and long-term data engineering roadmap.

You will ensure data quality, integrity, and security across all data assets, implementing best practices in data governance, documentation, and continuous improvement. Staying current with industry trends, you will introduce enhancements that elevate the organization’s analytical and data engineering capabilities.

In this working-leader role, you will contribute directly to coding, building, and maintaining production data solutions while also mentoring and supporting a growing team. You will lead by example—providing hands-on technical expertise, shaping engineering standards, and guiding the design and implementation of technology frameworks, programs, and policies.

This is a fully remote role.

What You'll do as a Lead Data Solutions Developer

Design, Build, and Maintain Data Pipelines / Solutions (60%)

• Design, build, test, and maintain robust data pipelines / solutions to support analytics and data science initiatives, ensuring efficient and reliable data flow.
• Define, develop, tests, and manage reporting-layer data objects, ensuring data is accessible and optimized for analysis.
• Maintain data pipelines schedules, orchestrates workflows, and monitors and troubleshoots data pipelines, ensuring smooth and efficient data flow and addressing any issues promptly.
• Optimize data storage and retrieval processes to enhance performance and scalability, ensuring data is readily available for analysis.
• Establish and maintain comprehensive data architecture and data integration documentation, including flows and transformations.
• Work with team members to solve complex data issues around data integration, unusable data elements, unstructured data sets, and other data processing incidents.
• Lead, manage, and develop a team of data solutions developers and data analysts.

Collaborate with Stakeholders and Ensure Data Quality (30%)

• Collaborate with business stakeholders to understand data requirements and deliver tailored data solutions that meet the needs of various business functions.
• Ensure data quality, integrity, and security across all data pipelines and reporting layers, implementing best practices for data management.
• Coordinate efforts to align data requirements across teams, ensuring smooth collaboration without requiring full-scale project management responsibilities.
• Provide technical guidance and support to team members and stakeholders, fostering a collaborative and knowledgeable environment.

Stay Current and Promote Data-Driven Culture (10%)

• Stay current with industry trends and advancements in data engineering and analytics, applying new techniques and technologies to improve data capabilities.
• Promote a data-driven culture within the organization, advocating for the use of data in decision-making processes.
• Mentor and develop junior team members, fostering a collaborative and high-performing team environment
• Support the development of data literacy within the organization, providing training and resources to help team members understand and utilize data effectively.
• Collaborate with the analytics team to ensure alignment and integration of data initiatives across the organization.

The Experience, Skills and Abilities Needed

Required:

• Bachelor’s degree in computer science, Math, Statistics, Software Engineering, or related field.
• Minimum 10 years’ experience of overall technical and/or data engineering experience including:
• Minimum 8 years' experience with SQL coding, including ability to build and maintain data pipelines and manipulate large datasets.
• Minimum 8 years' experience with data warehousing and ETL processes, ensuring efficient data storage and retrieval.
• Minimum 5 years' experience with programming languages such as Python and Scala, for developing data solutions.
• Minimum 5 years' experience with big data platforms such as Databricks and Snowflake.
• Minimum 5 years' experience with data modeling and data architecture, ensuring data is structured and optimized for analysis.
• Minimum 3 years' experience with Agile engineering practices and using DevOps tools.

Preferred:

• Up-to-date knowledge of data analytics tools and techniques, including familiarity with the latest advancements in the field.
• Ability to leverage both structured and unstructured data sources to extract meaningful insights and drive business decisions.
• Experience with Data Warehouse, Data Lakes, and BI systems, including extensive experience in collecting business requirements and transforming these into actionable analytics projects.
• Proficiency with reporting tools such as Tableau, Power BI, and SSRS, for creating and delivering insightful reports and dashboards.
• Knowledge of relational SQL databases and SQL, including experience with Oracle, Microsoft SQL Server, and MySQL.
• Ability to write functional specifications for data-related processes, workflows, architectures, business rules, and interfaces, and create design specification documents in consultation with Customers.
• Experience participating in project governance for Data and Analytics projects, working closely with Project Managers to ensure successful implementation.

Other:

• Strong analytical and problem-solving skills, enabling the identification and resolution of data-related challenges.
• Proven ability to understand our business and contribute technical solutions that drive measurable business outcomes.
• Ability to communicate complex data insights effectively to both technical and non-technical audiences, ensuring clarity and understanding.
• Excellent verbal, written, and visual presentation skills, capable of conveying data insights and recommendations in a compelling manner.
• Ability to work independently and within a team, establishing objectives, project plans, and milestone goals to drive projects to successful completion.
• Expertise in working with data to identify patterns, trends, and insights, informing business decisions and strategies.
• Ability to rapidly acquire new knowledge and learn new skills, staying current with industry trends and advancements.
• Ability to understand business needs and deliver results that have a clear, positive, and direct impact on the organization.
• Ability to persuade others by creating a compelling business case, addressing all relevant factors to gain buy-in and support for data initiatives.
• Ability to identify and assess relative costs and benefits of potential actions, choosing the most appropriate course of action to achieve business objectives.

What STERIS Offers