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Senior Databricks Engineer

1 month ago

Houston, Texas, United States Neudesic, an IBM Company Full time

About Neudesic, an IBM Company

Driven by a passion for technology and innovation, we deliver quality solutions that help our customers succeed. With decades of experience, proven frameworks, and a disciplined approach, we quickly deliver reliable, high-performing solutions that drive business growth.

Our team is built on core values that define who we are: Passionate about what we do, Disciplined in everything we undertake, Innovative by nature, committed to Teamwork, and conducting ourselves with Integrity. If these attributes resonate with you, let's discuss how you can contribute to our success.

Data and AI Practice Overview

We are seeking experienced Senior Databricks Engineers to join our Data and AI Practice. The ideal candidates will have extensive hands-on experience building scalable data pipelines and performing advanced analytics using Databricks. This role will focus on leveraging Apache Spark and Databricks to process and analyze large datasets, implement ETL workflows, and collaborate with cross-functional teams to deliver optimized data solutions.

Key Responsibilities:

  • Design, build, and maintain scalable ETL/ELT data pipelines using Azure Databricks and Apache Spark
  • Integrate data from various data sources such as Azure Data Lake, SQL databases, API services, and cloud storage
  • Automate data ingestion, cleansing, transformation, and validation processes
  • Leverage Databricks to perform large-scale data processing and distributed computing
  • Optimize and tune Apache Spark jobs to handle high-volume data workloads efficiently
  • Collaborate with other data team members and analysts to develop advanced analytics and machine learning workflows
  • Work closely with business analysts, data architects, and product teams to understand business requirements and translate them into technical solutions
  • Provide technical expertise and guidance on Databricks architecture, best practices, and troubleshooting
  • Monitor and optimize Databricks clusters for cost and performance efficiency
  • Troubleshoot performance bottlenecks, memory, and data storage issues in Spark applications
  • Integrate Databricks with Azure Data Lake Storage, Azure Synapse Analytics, and other Azure services for a seamless data ecosystem
  • Set up and manage Databricks Delta Lake for managing large-scale, real-time, and batch data pipelines
  • Design and implement automated testing and deployment workflows using Azure DevOps, Git, and Databricks APIs
  • Build and maintain CI/CD pipelines for Databricks jobs, notebooks, and workflows

Salary Estimate: $140,000 - $170,000 per annum (depending on location)

Requirements and Qualifications:

  • 3+ years of hands-on experience with Databricks and Apache Spark for big data processing
  • Experience monitoring and troubleshooting performance bottlenecks, tuning Databricks clusters for optimal performance and best practices of Databricks implementations
  • Extensive experience in Databricks Development & Engineering to include pipeline development, orchestration, design and optimization of notebooks and workflows in Databricks to support ETL (Extract, Transform, Load) operations
  • Strong proficiency in Python, SQL, and Scala for data engineering tasks
  • Experience with Azure services, particularly Azure Data Lake Storage, Azure Synapse, and Azure Blob Storage
  • Excellent communication skills and ability to collaborate with cross-functional teams

Benefits:

  • Award-winning company culture
  • Competitive salary and benefits package
  • Professional development opportunities
  • Diverse and inclusive work environment