Analytics Engineer

Could you be a good fit? We are looking for a highly skilled Analytics Engineer to join the team of our exceptional client. This role focuses on building and maintaining scalable data pipelines, integrating complex data sources, and creating trusted datasets that power analytics, reporting, dashboarding, and advanced business insights.

This position is ideal for a data professional who enjoys working across cloud platforms, APIs, marketing technologies, and enterprise systems to transform raw data into meaningful, business-ready information. The ideal candidate will bring strong Python and SQL skills, experience working with modern cloud data platforms, and a passion for building reliable, well-documented data solutions.

Benefits Healthcare Medical, Dental, and Vision Insurance 401k

What will your day look like? As an Analytics Engineer , you will:

• Design, develop, and maintain scalable data pipelines that ingest and integrate data from marketing platforms, enterprise systems, APIs, and CRM solutions
• Build and optimize data transformations and models that support reporting, dashboarding, analytics, and business intelligence initiatives
• Develop API-based integrations and custom Python solutions to automate data ingestion and processing workflows
• Ensure data quality, accuracy, and reliability through validation, monitoring, testing, and troubleshooting activities
• Create and maintain trusted datasets that support downstream reporting, analytics, and advanced modeling needs
• Collaborate with business stakeholders and technical teams to understand data requirements and deliver scalable solutions
• Develop and maintain technical documentation, metadata, data definitions, and data lineage information
• Support data governance initiatives and promote best practices related to data quality and usability
• Structure datasets and supporting documentation to support AI, machine learning, and emerging LLM use cases
• Leverage modern AI-enabled tools to improve engineering efficiency, troubleshooting, testing, and documentation workflows
• Work alongside other data professionals to support evolving business and analytics requirements

You will be a good fit for this role if you have:

• 5+ years of experience in Analytics Engineering, Data Engineering, or a similar data-focused role
• Strong SQL skills with experience building and supporting production-grade data solutions
• Strong Python development experience
• Hands-on experience with at least one modern cloud data platform, including:
  • Databricks
  • Snowflake
  • BigQuery
• Experience building and supporting REST API integrations
• Experience working with authentication, pagination, schema management, error handling, and monitoring within API workflows
• Experience working with marketing analytics, marketing data, or marketing technology ecosystems
• Experience integrating and modeling data across CRM, campaign, customer, media, or digital marketing platforms
• Experience working with Salesforce data and understanding CRM data relationships and structures
• Strong understanding of data modeling, data warehousing, and data engineering best practices
• Experience supporting downstream analytics, reporting, dashboarding, and business intelligence initiatives
• Experience with data validation, testing, monitoring, and troubleshooting production data pipelines
• Strong documentation skills including metadata management, data lineage, and data definitions
• Experience leveraging AI tools within engineering workflows for development, testing, debugging, analysis, and documentation
• Strong problem-solving, analytical, and communication skills

Nice-to-Haves Experience with Rivery and/or Boomi Experience preparing datasets and documentation for AI, machine learning, or LLM-driven applications Familiarity with Retrieval-Augmented Generation (RAG) or agent-based AI use cases Experience with BI and visualization tools such as: Power BI Tableau Looker Experience with advanced analytics, predictive modeling, or machine learning initiatives Knowledge of customer identity resolution and customer data platforms Experience with marketing attribution, campaign measurement, and marketing performance analytics Experience with data privacy, consent management, and customer data governance Experience supporting enterprise analytics programs in cloud environments

What Makes Someone Successful in This Role? The strongest candidates are data professionals who can bridge the gap between engineering, analytics, and business needs. Successful candidates typically bring:

• Strong SQL and Python expertise
• Experience with marketing and customer-related data
• Cloud data platform experience (Databricks, Snowflake, or BigQuery)
• API integration and data pipeline development experience
• A passion for creating trusted, well-documented datasets
• A strong focus on data quality, governance, and reliability
• An interest in AI-enabled engineering and analytics solutions

This role is an excellent fit for someone who enjoys building the foundational data assets that enable analytics, reporting, AI, and business decision-making.

About OpenKyber OpenKyber is a specialized staffing and consulting firm focused on IT and technology positions. Our deep industry knowledge allows us to match exceptional candidates with organizations where they can thrive and make an immediate impact.

Our Vision: To promote and foster the growth of information technology (IT) in our world-one candidate, one client, one community at a time.

Our Goal: To guide clients and candidates through the placement process and build long-term, successful relationships.

Our Culture: At OpenKyber, we value excellence, respect, and empathy in everything we do.

Sound like you? Ready to build scalable data solutions that drive analytics, reporting, and AI innovation? Click "Apply Now" and let"s start the conversation!

For applications and inquiries, contact:View email address on us.fitly.work