ETIC, Data Engineer Support, Senior Associate

AI in this role

databricks

Line of Service

Advisory

Industry/Sector

Technology

Specialism

Advisory - Other

Management Level

Senior Associate

Job Description & Summary

We are looking for a Data Engineer (Support) with strong expertise in the Microsoft Azure Cloud ecosystem to ensure the smooth operation, reliability, and scalability of our data infrastructure. This role will focus on monitoring, troubleshooting, and optimizing data pipelines and Azure data services while collaborating with data teams to support analytics and business intelligence functions.This role requires a strong understanding of cloud data architecture, hands-on experience with Azure data services (including Microsoft Fabric), and deep practical knowledge of Databricks for batch and data engineering.

Key Responsibilities
• Provide production support for Azure-based data pipelines, data lakes, and data warehouses.
• Monitor and resolve data ingestion, transformation, and performance issues across Azure Data Factory, Databricks, Synapse, and other services.
• Manage and troubleshoot ETL/ELT processes, ensuring data reliability and availability.
• Implement and maintain data quality checks, validation frameworks, and alerting systems.
• Collaborate with data engineers and business teams to analyze and fix data discrepancies.
• Develop scripts or automation tools using Python or PowerShell to improve operational efficiency.
• Participate in on-call rotations for incident management and escalation support.
• Maintain detailed documentation of data workflows, configurations, and incident resolutions.
• Suggest and implement process improvements to enhance reliability and reduce manual interventions.

⸻

Required Skills and Qualifications
• Bachelor’s degree in Computer Science, Information Systems, or related field.
• 3+ years of experience in data engineering, data platform operations, or production support.
• Strong expertise in Microsoft Azure Cloud, including:
• Azure Data Factory (ADF)
• Azure Synapse Analytics
• Azure Databricks
• Azure Data Lake Storage (ADLS)
• Azure Monitor / Log Analytics / Application Insights
• Proficiency in SQL for querying and debugging data issues.
• Experience with Python or PowerShell for automation and data processing.
• Familiarity with DevOps tools (Azure DevOps, Git, CI/CD pipelines).
• Understanding of data modeling, ETL concepts, and data warehousing principles.
• Strong problem-solving, communication, and incident management skills.

⸻

Preferred Qualifications
• Azure certifications such as:
• Microsoft Certified: Azure Data Engineer Associate (DP-203)
• Azure Administrator Associate (AZ-104)
• Experience with Databricks job orchestration, Delta Lake, or Spark.
• Familiarity with ITIL processes or structured incident/change management frameworks.
• Experience supporting real-time data streaming using Azure Event Hubs or Kafka.

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Not Specified

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date

How we score this

ETIC, Data Engineer Support, Senior Associate at PwC scores 9 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 1. The work itself involves no AI, or AI only appears as scenery, such as a company tagline.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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