$113K - $135.70K/yr
Full-time
Posted 21 days ago
Job description
As an employee-owned company, DMA prioritizes employees. Low turnover rates and tenured teams are living proof:
- 2025 Great Places to Work Certified
- Employee stock ownership program eligibility begins on day one of employment (ESOP contribution is targeted at 6% of your annual compensation)
- Company paid parental leave
- Generous time off package
- Multiple benefit plans, eligibility begins on day one of employment
- Culturally focused on work/life balance, mental health, and the overall wellness of our employees
This is a hybrid position with an expectation to be in our Fort Wayne, IN office a minimum of two days per week. This position does not qualify for relocation assistance. Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. This position does not qualify for employment-based sponsorship.
Position Summary
The Data Analyst will be primarily responsible for creating and maintaining DMA's infrastructure and systems that enable the collection, storage, and processing of data. This role is essential for ensuring data is accessible, reliable, and optimized for analysis and decision-making.
Essential Duties and Responsibilities
Design, build, and maintain robust data pipelines and ETL processes to ingest, transform, and deliver data from various sources.
Mine data from primary and secondary sources, then reorganize said data in a format that can be easily read by either human or machine
Use statistical tools to interpret data sets, pay particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts
Collaborate with programmers and engineers to improve efficiency and data organization; improve performance through data structure and query optimization
Ensure data integrity, quality, and security across all systems and platforms
Work with departments to provide insight and identify opportunities, improvements, recommend system modifications, and develop policies for data governance
Integrate structured and unstructured data from internal and external sources.
Monitor and troubleshoot data workflows, resolving issues proactively
Design, implement, and maintain critical data systems from ETL/ELT, Data Warehouse, BI Tools, and everything in between
Maintain documentation for data architecture, processes, and standards
Collaborate with data scientists, analysts, and product teams to support data needs.
Analyze requirements from the business and provide solutions or guidance for solutions
Work with senior data analyst to establish data governance
Non-Essential Duties and Responsibilities
Perform other duties as assigned
Education and Qualifications
Bachelor's degree in computer science, information systems, engineering, or related field.
2 to 5 years' experience as a data engineering role
Familiarity with professional programming preferred
Familiarity with relevant business domains
Ability to analyze large datasets and write comprehensive reports
Experience in data models and reporting packages
Experience working with data and data analytics development, preferably within the Microsoft data platform
Ability to understand business needs and translate them into technical solutions
Works effectively with analysts, stakeholders, and IT teams to deliver data solutions that drive business value
Proficiency in SQL and experience with relational and non-relational databases
Proficient with ELT/ETL and Data Warehousing development
Knowledge of relational databases and object-relational mapping concepts
Commitment to data quality, governance, and compliance
Understanding of data modeling, normalization, and schema design
Excellent organizational skills: ability to handle multiple projects
An analytical mind and inclination for problem-solving
Strong verbal and written communication skills
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The Company is an equal employment opportunity employer and is committed to providing equal employment opportunities to its applicants and employees. The Company does not discriminate in employment opportunities or practices on the basis of race, color, religion, gender, national origin, citizenship, age, disability, veteran status, genetic information, or any other category covered by applicable federal, state, or local law. This equal employment opportunity policy applies to all employment policies, procedures, and practices, including but not limited to hiring, promotion, compensation, training, benefits, work assignments, discipline, termination, and all other terms and conditions of employment.
It is DMA's policy to make reasonable accommodations for qualified individuals with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please contact our Human Resources team at HRDepartment@dmainc.com or 800-309-2110 and choosing selection 6.
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Software Engineer?
A: To succeed as a Data Software Engineer, key technical skills include proficiency in programming languages such as Python, Java, or C++, as well as expertise in data structures, algorithms, and software development methodologies like Agile. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Software Engineers often work with cross-functional teams and stakeholders to design, develop, and deploy data-driven solutions. By combining technical expertise with strong soft skills, Data Software Engineers can effectively drive business outcomes, innovate, and adapt to the rapidly evolving landscape of data technology.
Q: What is the career path for a Data Software Engineer?
A: A Data Software Engineer's typical career progression involves starting as a Junior Software Engineer, where they focus on developing and maintaining data-driven software applications, and gradually advancing to roles such as Senior Software Engineer, Technical Lead, or Data Architect, where they oversee large-scale data systems and lead cross-functional teams. Key opportunities for skill development include learning programming languages like Python, SQL, and Java, as well as data science tools like Hadoop, Spark, and machine learning frameworks like TensorFlow and PyTorch. Long-term, Data Software Engineers may pursue leadership roles, such as Director of Engineering or Chief Technology Officer, or transition into related fields like data science, product management, or entrepreneurship.
