Data Analyst - Custom Software

SPARK Business Works•Grand Rapids, MI

11d•$75,000 - $85,000

About The Position

As a Data Analyst supporting SPARK’s custom software, you will play a critical role in designing, building, and optimizing modern data solutions for our clients. You will help architect scalable data environments that support decision-making, analytics, and application performance. From raw data ingestion to strategic insight, you will contribute to creating reliable data systems that drive accountability and measurable business impact across the entire data lifecycle. In this role, you will collaborate closely with developers, project managers, and stakeholders to design sustainable data architecture that aligns with custom software solutions. You will build scalable ETL and ELT pipelines, ensure data systems are reliable, performant, and cost-efficient, and transform complex datasets into clear, actionable insights that help clients make informed decisions. Some travel may occasionally be required to meet with clients and project teams.

Requirements

5+ years of experience in data analytics, data engineering or a related role.
Extensive hands-on experience with Azure Data Factory, Databricks, Microsoft Fabric, and AWS Glue.
Strong knowledge of data warehouse and data lake architecture.
Experience building and maintaining ETL or ELT pipelines.
Proficiency in SQL and at least one scripting language such as Python.
Experience working within Azure and AWS cloud ecosystems.
Experience working with APIs, including RESTful services, authentication methods, data ingestion, and integration patterns.
Strong analytical skills with attention to detail and data accuracy.
Clear communicator who translates technical insights into business value.
Self-directed and collaborative, able to manage multiple priorities.

Nice To Haves

Direct software development experience, especially application code or full-stack environments.
Experience with modern BI tools and dashboard platforms.
Familiarity with CI CD practices in data environments.
Understanding of data governance and security best practices.
Exposure to DevOps workflows within software development teams.
Demonstrated ability to use AI-powered tools to improve efficiency, automate routine tasks, and enhance data analysis.

Responsibilities

Design, build, and maintain robust ETL and ELT pipelines.
Develop and manage scalable data warehouse and data lake solutions.
Ensure data integrity, reliability, and performance across systems.
Optimize data storage, transformation, and retrieval processes.
Implement data modeling best practices for analytics and reporting environments.
Translate complex datasets into actionable insights.
Develop dashboards, reports, and visualizations that support business decision-making.
Partner with stakeholders to define KPIs and measurement frameworks.
Validate data accuracy and troubleshoot inconsistencies.
Work cross-functionally with software developers and project managers to support application development and client solutions.
Assist in designing data architecture that aligns with custom software builds.
Provide input on data strategy, governance, and best practices.
Document data flows, transformations, and system architecture clearly and thoroughly.
Monitor data systems for performance bottlenecks.
Recommend and implement improvements for efficiency and scalability.
Support cloud cost optimization initiatives across Azure and AWS environments.