REQUIREMENTS

• Bachelor’s degree in a relevant field (e.g., Computer Science, Data Analytics, Statistics, or Information Systems) or equivalent experience in another engineering discipline.
• 5+ years of experience in data analysis, analytics implementation, or business intelligence, including at least 2 years in a lead or supervisory role.
• Strong experience with data platforms, ETL/ELT pipelines, and relational databases (Snowflake, SQL Server, PostgreSQL, Oracle, etc.).
• Proficiency in SQL and scripting languages such as Python or R for data processing, automation, and analysis.
• Experience with data visualization tools such as Tableau, Power BI, or similar.
• Familiarity with collaboration and productivity tools such as Git, Jira, Confluence, and Slack in an Agile environment.
• Solid understanding of Agile software development life cycle and methodology.
• Excellent technical writing skills, including documenting business requirements, development specifications, and user guides.
• Excellent communication and presentation skills, with the ability to convey technical information clearly to clients and internal stakeholders.
• Proven track record of successfully implementing software applications or data projects end-to-end.
• Demonstrated ability to drive projects by asking the right questions, understanding business requirements, and translating them into actionable development tasks.
• Experience working with offshore teams and managing distributed collaboration effectively.
• Strong organizational skills with the ability to prioritize competing demands and balance short-term needs with long-term goals.

PREFERRED EXPERIENCE

• Understanding of cloud platforms such as AWS
• Experience in working with financial institutions such as Credits Unions and Banks
• Experience with Jira, Confluence, Bitbucket
• Knowledge of prompt engineering techniques and experience using Generative AI tools (e.g., for code assistance, documentation, or workflow automation) to improve engineering productivity and innovation

• Lead and oversee data analysis and implementation activities for ancillary Arkalytics projects.
• Collaborate with Implementation Managers to define project milestones, ensure deliverables are met on time and within budget, and proactively address client issues.
• Serve as the primary point of contact for clients on all Arkalytics Business Conformance (BCON) and Visualization implementation matters and escalations.
• Facilitate requirements sessions, user training, and other client-facing meetings.
• Gather and document requirements for data pipeline integrations (ELT) and business logic data mappings.
• Document and review Source-to-Target Mappings (STTM).
• Partner with Solution Architects to define and implement best-in-class technologies and practices across Arkalytics where applicable.
• Provide hands-on technical leadership for the development and review of code across the business conformance and BI layers.
• Perform data profiling and analyze source system data and metadata.
• Develop, review, and test SQL code to support integrations and transformations.
• Test ELT workflows and provide sign-off to Implementation Engineers on source system integration work.
• Build and manage reference data for hierarchies, lookups, and groupings.
• Develop and maintain Data Dictionaries and Data Lineage documentation.
• Document processes, workflows, and templates to standardize and improve delivery.
• Develop and configure data visualizations using tools such as Tableau or Power BI.
• Manage, mentor, and coach analysts, fostering continuous learning and professional development.
• Participate in staffing decisions including hiring, onboarding, and performance management.
• Encourage innovation in areas such as data analysis, AI, stream processing, and cloud data services.
• Take ownership of challenges, apply creative problem-solving, and proactively remove roadblocks to guide the team to success.
• Ensure accuracy, completeness, and consistency of data transformations, mappings, and integrations.
• Identify and escalate data or process issues and risks in a timely and transparent manner.
• Additional responsibilities as assigned.