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Overnight Databricks Data Engineer Jobs in Vermont

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate ... Experience working within data platforms like Databricks/Snowflake, and analytics modeling ...

Provide cabling support and run cables within data centers, LAN rooms and remote wiring closets ... Must possess experience of system engineering in one or more areas including telecommunications ...

Ensure data integrity, security, and compliance within Workday Financials Integration & Data ... Opportunity to work closely with engineering, IT, and operations * Mission-driven organization ...

Ensure data integrity, security, and compliance within Workday Financials Integration & Data ... Opportunity to work closely with engineering, IT, and operations * Mission-driven organization ...

This position requires extensive travel with frequent overnight stays. Your Key Responsibilities ... About Stantec: Stantec is a global leader in sustainable engineering, architecture, and ...

Showing results 21-39

Overnight Databricks Data Engineer information

What is an overnight Databricks data engineer?

An Overnight Databricks Data Engineer is a professional who works primarily during night shifts to manage, design, and maintain big data pipelines and workflows using Databricks, a cloud-based data analytics platform. Their responsibilities often include developing and optimizing data processing jobs, ensuring data quality, and troubleshooting issues that arise during overnight data operations. This role is critical for organizations that require 24/7 data processing, continuous ETL jobs, or real-time analytics. Working overnight may also involve monitoring automated systems, performing scheduled data loads, and collaborating with global teams to ensure data availability and reliability.

What skills and qualifications are needed to thrive as an overnight Databricks data engineer?

To thrive as an Overnight Databricks Data Engineer, you need strong proficiency in data engineering, Python or Scala programming, and experience with big data technologies, typically supported by a relevant degree in computer science or a related field. Familiarity with Databricks, Apache Spark, cloud platforms (such as AWS or Azure), and certifications like Databricks Certified Data Engineer are highly valued. Attention to detail, problem-solving, and effective communication are essential soft skills, especially for troubleshooting and collaborating across shifts. These competencies ensure reliable data pipeline management and efficient resolution of issues during off-hours, maintaining seamless business operations.

What unique challenges do overnight Databricks data engineers face, and how can they be addressed?

Overnight Databricks Data Engineers often work with limited real-time support, which can present challenges when troubleshooting urgent data pipeline issues or system outages. To address this, it’s essential to develop strong problem-solving skills, document processes thoroughly, and leverage automated monitoring and alerting tools. Additionally, close collaboration with daytime teams during handoff periods ensures continuity and minimizes disruptions. Building a habit of proactive communication and maintaining detailed logs helps the entire team resolve issues efficiently and maintain data quality.

What is the difference between Overnight Databricks Data Engineer vs Data Engineer?

AspectOvernight Databricks Data Engineer
Work EnvironmentPrimarily remote or on-site, working overnight shifts to support global data operations
CertificationsDatabricks certifications, cloud platform credentials (AWS, Azure), data engineering certifications
Tools & TechnologiesDatabricks platform, Spark, cloud services, SQL, Python, ETL tools
Industry UsageTech, finance, healthcare, retail with 24/7 data needs

While both roles focus on data engineering, the Overnight Databricks Data Engineer specializes in managing data pipelines on the Databricks platform during overnight shifts, often supporting global operations. A Data Engineer may work across various platforms and shifts, with broader responsibilities in data architecture and pipeline development. The overnight role emphasizes specific platform expertise and shift timing, catering to organizations with continuous data processing needs.

Marketing Operations Analyst

Montpelier, VT

FocusKPI
Computing Infrastructure Providers, Data Processing, Web Hosting • 51 - 200 employees

Full-time

Re-posted 25 days ago


Job description

FocusKPI is looking for a Marketing Operations Analyst to join one of our clients, a high-tech SaaS company.

As a Marketing Operations Analyst on the Marketing Operations & Technology team, you’ll help share the client's marketing data strategy. This includes driving data governance and consistency across systems, enabling effective audience targeting for strategic marketing initiatives, and ensuring compliance with privacy regulations such as GDPR and CCPA. This is a hands-on technical role, ideal for someone who thrives in ambiguity, works autonomously with large data sets, and brings structure to complex problems. The role involves writing complex SQL to access data in our warehouse, while also building and activating audiences through our customer data platform (CDP). The ideal candidate is innately curious and passionate about identifying novel approaches to derive value from disparate data sets and highly motivated to improve your skillset around the modern data stack.

Responsibilities:

  • Audience Targeting: Develop and implement audience segmentation strategies using advanced SQL queries and data manipulation to support targeted campaigns.
  • Data Governance and Management: Gain a comprehensive understanding of our data quality and flow processes, while identifying and developing solutions to enhance data usability and accessibility.
  • Compliance Oversight: Ensure all marketing data practices adhere to privacy regulations, including GDPR and CCPA.
  • Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate data from various sources into the customer data platform (CDP) for comprehensive analysis.
  • Analytics and Reporting: Design and execute data analyses to derive actionable insights, providing stakeholders with regular reports on marketing performance and audience behaviour.
  • Collaboration and Communication: Collaborate cross-functionally with marketing stakeholders to gather evolving requirements, design effective solutions, and clearly communicate nuances of the deliverable to ensure alignment and actionable outcomes.

Requirements:

  • Bachelor’s degree in Data Science, Computer Science, or a related field
  • Minimum of 3-5 years of experience in data management, analytics, or similar, preferably within a marketing environment
  • Proficiency in SQL for data manipulation and analysis. Comfortable with Python.
  • Experience working within data platforms like Databricks/Snowflake, and analytics modeling platforms such as Tableau
  • Strong analytical and problem-solving skills with the ability to interpret complex data sets and generate actionable insights.
  • Exceptional attention to detail and a commitment to maintaining high data quality standards.
  • Demonstrates innate curiosity, comfort with ambiguity, and a proactive approach to identifying opportunities for improvement and innovation in data processes

No C2C resumes are considered


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About FocusKPI

Sourced by ZipRecruiter

Industry

Computing infrastructure providers, data processing, web hosting

Company size

51 - 200 Employees

Headquarters location

Santa Clara, CA, US

Year founded

2010