Data Analyst - Azure Databricks

Key Responsibilities

As a Data Engineer (The Builder) :

• Build the Data Platform: Design, build, and maintain our end-to-end data pipelines (ETL/ELT), ensuring data is extracted, cleaned, and loaded reliably from various sources into our data warehouse.
• Architect the Infrastructure: Choose and implement our core data infrastructure, including our cloud
  

• Ensure Data Integrity: Develop and implement robust data quality checks and monitoring to ensure the accuracy, consistency, and reliability of our data in line with governance standards.
• Manage Data Sources: Connect to and manage data from a variety of sources, including third-party APIs, application databases, and event logs.
  

As a Data Analyst (The Insight Generator)

• Drive Business Decisions: Proactively identify and answer key business questions using data. Perform deep-dive analyses to uncover trends, opportunities, and risks.
• Define and Track Metrics: Partner with product, marketing, and leadership teams to define and track critical business metrics and KPIs.
• Create Dashboards & Reports: Build and maintain clear, compelling dashboards and reports in our Business Intelligence (BI) tool to make data accessible to the entire organization.
• Present Findings: Communicate complex analytical findings to non-technical stakeholders in a clear and actionable a Data Governance & Lineage Lead
• Establish Data Governance: Lay the groundwork for our data governance program by defining core data ownership, quality standards, and access policies.
• Manage Data Lineage: Document and manage the data lineage from our source systems to our reports and dashboards to ensure data traceability and trust.
• Ensure Compliance: Help establish foundational security and privacy protocols for our data Qualifications :
• 3+ years of professional experience in a data-focused role (Data Analyst, Data Engineer, or similar).
• Strong proficiency in SQL for data analysis and modeling.
• Hands-on experience with a major cloud platform (AWS, GCP, or Azure).
• Experience in building and maintaining data pipelines using a scripting language like Python.
• Familiarity with data warehousing concepts and technologies (e.g., columnar databases, star schema).
• Experience with a BI tool such as Tableau, Power BI, Looker, or similar.
• Excellent communication skills with the ability to bridge the gap between technical data and business Skills (Nice to Have) :
• Experience with a workflow orchestration tool like Airflow.
• Experience with a data governance or data catalog tool (e.g., dbt, Apache Atlas).
• Familiarity with data governance principles and best practices.
• Experience in a B2B SaaS or e-commerce environment.
• Knowledge of basic statistical methods and A/B testing principles.