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Senior Data Engineer (Databricks, Azure)

Ascent·Salary not specified

Primary stack

Azure Service BusDatabricksPythonAzure Key VaultETLAzureAPIDelta LakeSQL

Nice to have's

Microsoft Cognitive Servicesevent-driven and microservices architecture patternsDatadogApplication InsightsAgile team collaborationDevOps practices

Job description

About the Position

If you like providing efficient, effective solutions to complex challenges, join us at Acuity! Be at the heart of helping achieve extraordinary things with software and data for our customers!

About Us

Ascent has recently been acquired by Acuity Analytics. This is both a significant milestone for us and a tremendous opportunity for you. Acuity Analytics is a business with a strong global reputation, an impressive client base, and ambitious growth plans. We deliver deep insights and domain-led digital transformation to high-growth and heavily regulated organizations. To our customers, we bring a partnership that provides the talent, technology, and capability to enhance performance and operational efficiency.

About the Role

We are looking for a skilled Data Engineer with strong experience in Databricks, Azure Cloud, and data orchestration to join our team. You will be responsible for designing, building, and managing scalable data solutions in a cloud-native environment, with a focus on automation, performance, and collaboration.

Key Responsibilities

  • Build and manage Databricks Workflows for large-scale data orchestration.
  • Develop and deploy PyFunc models and integrate them into production pipelines.
  • Implement secure secrets and configuration management using Azure Key Vault.
  • Automate data flows using Azure Logic Apps.
  • Design and optimize ETL / ELT pipelines in line with best practices.
  • Govern and manage data assets using Unity Catalog and Data Lakehouse patterns.
  • Implement messaging and event-driven workflows with Azure Service Bus.
  • Collaborate with architects, analysts, and data scientists to deliver end-to-end solutions.
  • Utilize Azure DevOps for CI/CD pipeline management.

Skills Required

Data Engineering & Orchestration

  • Databricks Workflows, Unity Catalog, Delta Lake
  • ETL/ELT design and implementation
  • Data Lakehouse architecture

Programming

  • Strong Python skills for data engineering, automation, and integration
  • Experience writing modular, production-ready code
  • CI/CD pipelines for Databricks and Azure

Databases

  • Strong knowledge of SQL (including query optimization and data modeling)
  • Exposure to NoSQL databases (e.g., Cosmos DB)

Azure Cloud Services

  • Azure Key Vault
  • Azure Logic Apps
  • Azure Service Bus
  • API Management (APIM)

Nice to Have

AI & Cognitive Services

  • Experience with Microsoft Cognitive Services (OCR, Layout, Form Recognizer, etc.)
  • Integration of cognitive services into data pipelines

Architecture & Monitoring

  • Familiarity with event-driven and microservices architecture patterns
  • Experience with monitoring tools like Datadog, Application Insights, or similar

Collaboration & Methodologies

  • Agile team collaboration
  • DevOps practices

Why Join Us

People are at the Heart of our Business. By investing in people, we achieve exceptional results for our clients and create new opportunities for our teams to thrive. Check out this page for more details.

If you have any questions, contact our Talent Acquisition team on ta.admin@acuityanalytics.

For more details about Acuity Analytics, please see here.

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Ascent

Software Product Development,Analytics and Data Science,IoT Solutions,AI

About the Company Ascent specializes in helping customers bridge the gap between their ambitions and reality. The company's data and software teams focus on creating revolutionary insights, operational strength, and competitive edge. Their expertise lies in software product development, analytics, data science, IoT solutions, and AI. Products, Services & Tech Stack Core Solutions: Software Product Development Analytics Data Science IoT Solutions AI Project Scope & Target Clients Client Base: Target verticals or client types served are not specified. Engineering Scale: Scope and complexity of engineering projects are not specified.

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