About Request Technology
Sourced by ZipRecruiter
Company size
1 - 10 Employees
Headquarters location
Naperville, IL, US
Year founded
1984
Other
Posted 28 days ago
Job description
NO SPONSORSHIP - NO OPT
Senior Associate, Data Analytics Engineering
SALARY: $117k - $120k plus 10% bonus
LOCATION: CHICAGO, IL
HYBRID: 3 days on site
3 years plus experience as a data engineer / software engineer. Looking for a data scientist with financial risk analyst experience, business intelligence analyst, complex analytical experience.
Responsibilities:
- Design and maintain analytics solutions drawing from both raw and semantic data layers
- Partner with business units to gather requirements and develop targeted analytics solutions
- Create data models ensuring information availability in the analytics warehouse for analysis and dashboard development
- Help establish Data Analytics standards and collaborate with embedded business analysts to ensure adherence
- Develop comprehensive documentation and testing protocols to guarantee data accuracy and accessibility
- Identify and distribute data and analytics best practices across the team
- Continuously expand knowledge of data and analytics engineering methodologies to enhance infrastructure maintainability and reliability
- Champion self-service capabilities and data literacy among business users through semantic layer utilization, analytics platforms (Tableau, Python), and CI/CD tools
- Pursue ongoing professional development in data analytics, cloud computing, options trading, and financial risk management to improve analytics infrastructure
- Provide guidance to business-embedded data analysts in addressing analytical challenges and support ad-hoc development needs
Qualifications:
Technical Skills:
- Ability to write and optimize complex analytical (SELECT) SQL queries
- Ability to write and optimize python for custom data pipeline code (virtual environments, scripts vs. modules vs packages, functional programming, unit testing)
- Strong Experience with data viz/prep tools (preferably Tableau and Alteryx)
- Experience with a source code version control repository system, branch management, pull requests (preferably Git)
Education and/or Experience:
- [Required] Bachelor's or Master s degree in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Physics, Data Science, Electrical Engineering, Information Systems) or equivalent professional experience
- [Required] 3+ years of experience as a data analyst, data engineer, software engineer, data scientist, financial risk analyst, business intelligence analyst
requesttechnology.com
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Analytics Developer?
A: To succeed as a Data Analytics Developer, key technical skills include proficiency in programming languages such as Python, R, or SQL, as well as expertise in data visualization tools like Tableau or Power BI, and familiarity with machine learning libraries like scikit-learn or TensorFlow. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Analytics Developers often work with cross-functional teams to identify business needs and develop data-driven solutions. By combining technical expertise with strong soft skills, Data Analytics Developers can effectively drive business growth, improve decision-making, and advance their careers in the field.
Q: What is the career path for a Data Analytics Developer?
A: A Data Analytics Developer's career path typically begins as a Junior Data Analyst or Data Analyst, where they develop foundational skills in data visualization, statistical modeling, and programming languages such as Python or R. As they gain experience, they progress to mid-level roles like Senior Data Analyst or Data Engineer, where they focus on designing and implementing large-scale data systems, and develop expertise in machine learning, data warehousing, and cloud computing. Ultimately, senior roles like Lead Data Scientist or Director of Data Analytics offer opportunities for leadership, strategic decision-making, and driving business outcomes through data-driven insights.
