IT Manager - Data Engineering & Analytics

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it , our most valuable asset is our people. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning; bold ideas; courage an d passion to drive life-changing impact to ZS.
Our most valuable asset is our people .
At ZS we honor the visible and invisible elements of our identities, personal experiences and belief systems-the ones that comprise us as individuals, shape who we are and
make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about.
IT MANAGER, DATA ENGINEERING AND ANALYTICS will lead a team of data engineers and analysts responsible for designing, developing, and maintaining robust data systems and integrations. This role is critical for ensuring the smooth collection, transformation, integration and visualization of data, making it easily accessible for analytics and decision-making across the organization. The Manager will collaborate closely with analysts, developers, business leaders and other stakeholders to ensure that the data infrastructure meets business needs and is scalable, reliable, and efficient.
What You'll Do:
Team Leadership:

• Manage, mentor, and guide a team of data engineers and analysts, ensuring their professional development and optimizing team performance.
• Foster a culture of collaboration, accountability, and continuous learning within the team.
• Lead performance reviews, provide career guidance, and handle resource planning.

Data Engineering & Analytics:

• Design and implement data pipelines, data models, and architectures that are robust, scalable, and efficient.
• Develop and enforce data quality frameworks to ensure accuracy, consistency, and reliability of data assets.
• Establish and maintain data lineage processes to track the flow and transformation of data across systems.
• Ensure the design and maintenance of robust data warehousing solutions to support analytics and reporting needs.

Collaboration and Stakeholder Management:

• Collaborate with stakeholders, including functional owners, analysts and business leaders, to understand business needs and translate them into technical requirements.
• Work closely with these stakeholders to ensure the data infrastructure supports organizational goals and provides reliable data for business decisions.
• Build and Foster relationships with major stakeholders to ensure Management perspectives on Data Strategy and its alignment with Business objectives.

Project Management:

• Drive end-to-end delivery of analytics projects, ensuring quality and timeliness.
• Manage project roadmaps, prioritize tasks, and allocate resources effectively.
• Manage project timelines and mitigate risks to ensure timely delivery of high-quality data engineering projects.

Technology and Infrastructure:

• Evaluate and implement new tools, technologies, and best practices to improve the efficiency of data engineering processes.
• Oversee the design, development, and maintenance of data pipelines, ensuring that data is collected, cleaned, and stored efficiently.
• Ensure there are no data pipeline leaks and monitor production pipelines to maintain their integrity.
• Familiarity with reporting tools such as Superset and Tableau is beneficial for creating intuitive data visualizations and reports.

Machine Learning and GenAI Integration:

• Machine Learning: Knowledge of machine learning concepts and integration with data pipelines is a plus. This includes understanding how machine learning models can be used to enhance data quality, predict data trends, and automate decision-making processes.
• GenAI: Familiarity with Generative AI (GenAI) concepts and exposure is advantageous, particularly in enabling GenAI features on new datasets. Leveraging GenAI with data pipelines to automate tasks, streamline workflows, and uncover deeper insights is beneficial.

What You'll Bring:

• 12+ years of experience in data engineering, with at least 3 years in a managerial role.
• Technical Expertise: Strong knowledge of data engineering concepts, including data warehousing, ETL processes, and data pipeline design. Proficiency in Azure Synapse or data factory, SQL, Python, and other data engineering tools.
• Data Modeling: Expertise in data modeling is essential, with the ability to design and implement robust, scalable data models that support complex analytics and reporting needs. Experience with data modeling frameworks and tools is highly valued.
• Leadership Skills: Proven ability to lead and motivate a team of engineers while managing cross-functional collaborations.
• Problem-Solving: Strong analytical and troubleshooting skills to address complex data-related challenges.
• Communication: Excellent verbal and written communication skills to effectively interact with technical and non-technical stakeholders. This includes the ability to motivate team members, provide regular constructive feedback, and facilitate open communication channels to ensure team alignment and success.
• Data Architecture: Experience with designing scalable, high-performance data systems and understanding cloud platforms such as Azure, Data Bricks.
• Machine Learning and GenAI: Knowledge of machine learning concepts and integration with data pipelines, as well as familiarity with GenAI, is a plus.
• Data Governance: Experience with data governance best practices is desirable.
• Open Mindset: An open mindset with a willingness to learn new technologies, processes, and methodologies is essential. The ability to adapt quickly to evolving data engineering landscapes and embrace innovative solutions is highly valued.

Perks & Benefits:
ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth and professional development. Our robust skills development programs, multiple career progression options and internal mobility paths and collaborative culture empowers you to thrive as an individual and global team member.
We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.
Travel:
Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.
Considering applying?
At ZS, we're building a diverse and inclusive company where people bring their passions to inspire life-changing impact and deliver better outcomes for all. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you don't meet 100% of the requirements listed above.
ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law.
To Complete Your Application:
Candidates must possess or be able to obtain work authorization for their intended country of employment.An on-line application, including a full set of transcripts (official or unofficial), is required to be considered.
NO AGENCY CALLS, PLEASE.
Find Out More At:
www.zs.com