Data Analytics Engineer

Key Responsibilities:

• Strategic Data Processing & Validation:
  Assist in creating and executing a strategic plan for efficient data processing and validation, under the direction of senior leadership. Help establish data governance policies to ensure long-term data integrity and scalability across multiple SaaS platforms.

• Data Model Development:
  Contribute to the creation and maintenance of data models for key business platforms (e.g., Salesforce, financial systems). Work closely with senior teams and FP&A to ensure data structures support financial forecasting and scenario analysis.

• Data Pipeline Creation & Optimization:
  Collaborate on the design and optimization of data pipelines that aggregate data from diverse sources. Ensure the data is accurate, accessible, and aligned with reporting needs while following best practices for data quality and governance.

• Automated Data Validation & Issue Resolution:
  Proactively identify and resolve data discrepancies by automating validation processes. Implement tools to monitor and maintain high data quality, reducing manual intervention and ensuring teams have access to accurate, validated data.

• Data Integration & Strategic Support:
  Play a key role in integrating data within platforms like Salesforce, Azure, or AWS, ensuring seamless data flow and consistency across systems. Lead technical efforts on data-centric projects, collaborating with key stakeholders to ensure infrastructure supports evolving business and financial reporting needs.

Qualifications:

• Experience: 3-5 years in data analysis, data modeling, business intelligence, or Salesforce administration with a focus on financial data environments.
• Technical Skills: Proficiency in SQL, with experience in data integration and pipeline tools such as Alteryx, Fivetran, Knime, or similar. Familiarity with Salesforce (including APEX), or other SaaS platforms, is a plus.
• Business Acumen: Strong understanding of financial reporting, metrics, and the ability to work in fast-paced financial or SaaS-driven environments.
• Analytical Skills: Demonstrated ability to create, implement, and maintain scalable data models and solve complex data problems.
• Certifications: Microsoft Certified: Data Analyst Associate, AWS Certified Data Analytics, Salesforce Administrator, or similar certifications are a plus.
• Education: Bachelor's degree in Data Analytics, Information Systems, Finance, or related field, or equivalent experience in data engineering or analytics (3-5 years).