Senior Associate, Data Analytics Engineering

Overview

We are seeking a data analytics professional to join a centralized analytics group responsible for strengthening enterprise-wide data capabilities. In this role, you will work closely with business stakeholders to understand analytical needs, translate them into technical solutions, and collaborate with data engineering teams to develop and maintain the internal analytics ecosystem.

You will build deep domain knowledge of the organization's data assets and help teams leverage these resources for reporting, dashboards, and advanced analysis. This position also contributes to shaping analytics standards and enabling self-service tools across the company.

Key Responsibilities

Analytics Solution Development

• Design, enhance, and maintain analytics assets built from both raw and curated data sources.
• Create scalable data models that support dashboards, KPIs, and exploratory analysis.
• Work with data engineering partners to evolve warehouse structures and ETL/ELT processes.

Business Partnership & Requirements Gathering

• Collaborate with a wide range of business units to define analytical requirements.
• Translate complex or vague business questions into structured, technical deliverables.
• Provide analysis guidance and hands-on support for high-priority initiatives.

Standards, Quality, & Documentation

• Contribute to establishing and promoting analytics and data modeling standards.
• Develop thorough documentation, testing plans, and validation checks to ensure accuracy and reliability.
• Share and reinforce best practices across analysts and technical teams.

Data Literacy & Self-Service Enablement

• Advocate for effective use of semantic layers, visualization tools, and scripting environments.
• Help non-technical users improve their ability to explore and understand data.
• Mentor embedded analysts and assist with ad‑hoc development challenges.

Continuous Learning & Improvement

• Stay current on modern data engineering and analytics practices to improve system maintainability.
• Expand knowledge in cloud platforms, data modeling, and analytic methodologies to help evolve the organization's analytics foundation.

Qualifications

Required Skills & Competencies

• Ability to collaborate cross-functionally with business partners, architects, governance teams, security, and IT operations.
• Strong communication skills for bridging technical and non-technical audiences.
• Attention to detail and structured problem‑solving abilities.
• Comfort supporting business analysts under tight timelines.

Technical Requirements

• Proficient in writing and optimizing advanced SQL queries.
• Strong Python development experience in analytics or pipeline use cases, including modularization and unit testing.
• Hands-on experience with data visualization and preparation tools (Tableau, Alteryx, or comparable platforms).
• Familiarity with version control workflows (Git, branching strategies, pull requests).

Preferred Technical Experience

• Exposure to transformation or semantic‑layer tools (e.g., dbt).
• Experience with cloud services (AWS, Azure) or cloud data platforms (Snowflake, Databricks).
• Knowledge of normalized and dimensional data modeling concepts (3NF, star schemas).
• Familiarity with workflow orchestration frameworks (Airflow, Dagster, Prefect).
• Understanding of applied statistics and experience using statistical methods in analysis.

Education & Experience

• Bachelor's or Master's degree in a quantitative or technical field (e.g., Data Science, Computer Science, Statistics, Engineering, Mathematics), or equivalent practical experience.
• Minimum of 3 years of experience in roles such as data analyst, data engineer, data scientist, BI analyst, software engineer, or similar.

Preferred Certifications

• Certifications related to analytics or BI tools.
• Financial or analytical professional certifications.