Full-Time

Senior Power BI/Azure Associate

SPS Holding

SPS Holding

Compensation Overview

$48 - $50/hr

New York, NY, USA

In Person

Category
DevOps & Infrastructure (1)
Required Skills
Power BI
Data Lake
Microsoft Azure
SQL
ETL
Databricks
Requirements
  • 6–10 years of experience in data development, analytics, or related engineering roles.
  • Deep expertise in Microsoft Power BI (DAX, Power Query, data modeling, visualization best practices).
  • Deep expertise in Azure Synapse Analytics (SQL, dedicated SQL pools, serverless query design).
  • Deep expertise in Azure Data Factory (pipelines, linked services, dataflows, parameterization).
  • Strong command of SQL, enterprise data warehousing concepts, and ETL/ELT methodologies.
  • Hands-on experience with Azure Data Lake, Azure Blob Storage, or equivalent cloud storage platforms.
  • Strong analytical, diagnostic, and problem-resolution capabilities.
  • Ability to thrive in an agile, fast-paced environment, adapting quickly to evolving business needs.
Responsibilities
  • Develop and maintain robust data pipelines using Azure Data Factory (ADF) or Azure Synapse for ingestion, transformation, and loading across diverse data sources.
  • Implement orchestration frameworks, parameterized pipelines, and automated monitoring to ensure reliability, scalability, and performance.
  • Troubleshoot, optimize, and enhance ETL workflows aligned with enterprise data standards.
  • Design and optimize data models using Azure Synapse Analytics or Azure Databricks to support analytical workloads and enterprise reporting.
  • Build star schemas, data lakehouse structures, and tune performance for large-scale datasets.
  • Partner with data architects to uphold data governance, lineage, and security compliance.
  • Develop dynamic, interactive dashboards and reports in Power BI that convert complex data into clear, actionable insights.
  • Build and maintain Power BI datasets, DAX measures, semantic models, and Row-Level Security (RLS).
  • Gather requirements and collaborate with business stakeholders to deliver intuitive, user-friendly visualizations.
  • Monitor data workflows for performance bottlenecks, reliability risks, and cost optimization opportunities.
  • Automate recurring data processes to improve operational efficiency and data quality.
  • Implement quality controls and validation frameworks for consistent, accurate reporting.
  • Work closely with Data Engineers, Analysts, and business partners to support enterprise analytics initiatives.
  • Produce detailed technical documentation, including pipeline configurations, data model designs, and dashboard specifications.
  • Contribute to best practices, standards, and continuous improvement efforts across the data organization.

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