Senior Data Analyst

Overview

Hybrid
$60 - $70
Contract - W2
Contract - 10 Month(s)

Skills

Access Control
Advanced Analytics
Amazon Web Services
Analytical Skill
Analytics
Artificial Intelligence
Business Process
Collaboration
Communication
Data Analysis
Data Governance
Data Modeling
Data Processing
Data Profiling
Data Quality
Data Structure
Data Validation
Databricks
Decision-making
Design Review
Documentation
Embedded Systems
Facilitation
Forecasting
Functional Requirements
Informatica
Predictive Modelling
Product Requirements
Regulatory Compliance
Semantics
Machine Learning (ML)
Mentorship
Meta-data Management
Pivotal
SQL
Mapping
Snow Flake Schema
Specification Gathering
Use Cases
User Stories
Workflow

Job Details

Senior Data Analyst

Hybrid > 3 DAYS/WEEK ONSITE IN BURBANK

10 Months Contract

Summary

The Senior Data Analyst plays a pivotal role in shaping that foundation - translating product requirements into robust, scalable data models that serve both immediate application needs and long-term analytical and AI objectives.

Embedded within the Platform POD, this role works closely with Application Designers, Platform Engineers, the Senior Data Architect, and product-aligned pods to ensure application-specific data models integrate seamlessly with the enterprise data platform. They act as the primary bridge between feature-level requirements and platform-level data strategy ensuring reusability, governance compliance, and analytical readiness.

Responsibilities

  • Lead data Analysis for application and platform alignment.
  • Translate product features and user stories into well-defined data model requirements that support application workflows and downstream analytics.
  • Partner with Application Designers and Engineers to profile, assess, and validate source data, ensuring it meets both functional and non-functional requirements.
  • Collaborate with the Senior Data Architect to align application data models with canonical and semantic models across domains.
  • Ensure long-term analytical and AI enablement.
  • Design data structures and pipelines that serve both operational application needs and future analytical/AI use cases.
  • Anticipate and define data capture, transformation, and enrichment requirements to support predictive modeling, forecasting, and advanced analytics.
  • Recommend optimizations that improve data quality, timeliness, and completeness for decision-making.
  • Partner with enterprise data governance teams to apply metadata, lineage, and access control standards.
  • Define and execute data validation, profiling, and reconciliation processes to ensure trusted results.
  • Maintain documentation of data definitions, mapping specifications, and lineage diagrams for both applications and analytical datasets.
  • Lead cross-POD workshops to resolve semantic conflicts, promote reusable data assets, and ensure consistent application of standards.
  • Mentor junior analysts and support teams in data discovery, mapping, and quality assessment best practices.
  • Represent the Platform POD s data perspective in architecture boards, product councils, and design reviews.

Requirements

  • 7-10+ years of proven expertise in data modeling techniques (relational, dimensional, wide-table for ML, data vault) and mapping business processes to data structures
  • 7-10+ years of strong proficiency in SQL, data profiling, and transformation tools (e.g., dbt, Informatica, AWS Glue)
  • 7-10+ years of familiarity with distributed data processing and analytics platforms (e.g., Snowflake, Databricks, AWS-native analytics stack)
  • 7-10+ years of experience translating product features and user stories into well-defined data model requirements

Functional Knowledge / Skills

  • Design data solutions that reflect business semantics and scale across use cases.
  • Translate analytical needs into technical specifications and vice versa.
  • Make governance easy to adopt by embedding it directly into design and workflows.
  • Anticipate future analytical and AI needs when designing today s application data structures.
  • Work across functions to raise the quality, reusability, and reliability of data.
  • Excellent communication and facilitation skills to influence design decisions across product, platform, and governance teams.

Technology Requirements

  • Proven expertise in data modeling techniques (relational, dimensional, wide-table for ML, data vault) and mapping business processes to data structures.
  • Strong proficiency in SQL, data profiling, and transformation tools (e.g., dbt, Informatica, AWS Glue)
  • Experience in data quality frameworks, validation automation, and reconciliation methods.
  • Familiarity with distributed data processing and analytics platforms (e.g., Snowflake, Databricks, AWS-native analytics stack)
  • Demonstrated ability to align cross-team requirements into unified, reusable, and governed data solutions.
  • Experience Translating product features and user stories into well-defined data model requirements.

Education

N/A

The estimated pay range for this position is USD $70.00/hr - USD $75.00/hr. Exact compensation and offers of employment are dependent on job-related knowledge, skills, experience, licenses or certifications, and location. We also offer comprehensive benefits. The Talent Acquisition Partner can share more details about compensation or benefits for the role during the interview process.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Milestone Technologies, Inc.