Position Overview

We are seeking a detail-oriented Data Analyst who will ensure that organizational data is
accurately transformed, validated, and prepared for downstream consumption.

Key Responsibilities

Data Transformation & Integration

Design, develop, and maintain ETL/ELT pipelines to consolidate data from disparate systems (databases, APIs, flat files)
Apply business logic to normalize, enrich, and standardize incoming datasets

Data Quality Assurance

Implement validation rules and automated tests to ensure accuracy, consistency, and completeness of data in the unified data store
Monitor data pipelines for anomalies or failures and initiate corrective actions

Data Completeness & Ingestion Oversight

Identify and flag missing or incomplete records prior to ingestion
Collaborate with data engineering teams to resolve data gaps and reprocess source feeds as needed

Reporting & Analytics Support

Produce ad-hoc analyses, dashboards, and visualizations to help stakeholders make data-driven decisions
Translate complex data findings into clear, actionable recommendations

Documentation & Governance

Maintain comprehensive documentation of data models, ETL processes, data definitions, and data lineage
Contribute to data governance initiatives, including metadata management and glossary upkeep

Process Improvement & Automation

Continuously evaluate and optimize existing workflows for efficiency, scalability, and reliability
Develop scripts or lightweight tools to automate repetitive data-validation tasks

Cross-Functional Collaboration

Partner closely with Business Analysts, Data Engineers, and Data Scientists to understand requirements and deliver high-quality datasets

Required Qualifications

Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field
8+ years of hands-on experience in data analysis, data engineering, or a similar role
Proficiency in SQL for data extraction, transformation, and validation
Experience with ETL/ELT tools or frameworks (e.g., Azure Data Factory, AWS Glue, Apache Airflow)
Strong analytical mindset with meticulous attention to detail

Preferred Qualifications

Familiarity with programming/scripting languages such as Python
Experience with cloud data platforms (AWS, Azure, or GCP) and data warehousing solutions (Snowflake, BigQuery)
Hands-on knowledge of BI tools (Tableau, Power BI, Looker) for dashboard development
Understanding of data modeling, normalization, and dimensional design
Prior exposure to big data technologies (Spark, Hadoop)

Skills & Competencies

Analytical Thinking: Able to dissect complex problems and devise logical solutions
Problem Solving: Proactively identifies issues and implements corrective measures
Collaboration: Works effectively across teams to deliver shared objectives
Adaptability: Thrives in fast-paced environments and embraces new technologies
Documentation: Champions clear, concise, and up-to-date process documentation