Analytics Engineer

• Design and develop data serving and semantic layers to support business needs ranging from traditional reporting to reverse ETL and LLM/AI implementations.
• Develop data models for use by analysts and applications from across the business using modern dimensional modeling practices to efficiently serve accurate, consistent data.
• Build and maintain robust, scalable data pipelines to extract, transform, and load (ETL, ELT) data from various sources into the data platform using both batch processing and event-driven patterns.
• Create efficient, performant data models to support business requirements and analytics needs.
• Implement and automate data quality checks and monitoring to ensure data accuracy and drive observability.
• Manage, troubleshoot and optimize existing data infrastructure, including cloud-based solutions and on-premises systems.
• Leverage cloud data platforms (Fabric, Databricks, Snowflake, etc.) for data storage, processing, and analysis.
• Work closely with data analysts, data scientists, and business stakeholders to understand their data needs and deliver solutions.
• Identify and resolve data-related issues and challenges for technical and non-technical stakeholders.
• Support company-wide projects ranging from server migrations to mergers and acquisitions as a data and systems expert.
• Automate data processes to improve efficiency and reduce manual effort.
• Implement modern concepts like metadata-driven pipelines and Infrastructure-as-Code that will play a key role in a scalable, resilient data platform.
• Document data processes, architecture, and workflows.

• Architect, Design and implement ETL processes.
• Develop and maintain integration tools and utilities.
• Proficient in writing SQL queries and troubleshooting issues.
• Support existing applications.
• Provide guidance and support to Junior/Mid-level developers.
• Instruct, direct, and check the work of others.
• Lead, design, code, test and debug complex development efforts.
• Document, enforce and model best standards and practices to others.
• Oversee project completions and ensure user satisfaction.
• Complies with Company policies, procedures, regulatory requirements, and complete mandatory company compliance training by prescribed deadlines.
• Ability to accept guidance and supervision from management.
• Other duties that may be reasonably assigned.

Senior ETL Developer

• Build a strong understanding of business processes, data flows, and key metrics to analytics outputs align with real business needs
• Partner closely with business teams and analytics stakeholders to clarify requirements, definitions, and reporting logic
• Support the translation of existing DOMO ETL pipelines and business logic into SQL based transformations on the modern data platform
• Write, maintain, and improve SQL transformations with a focus on correctness, clarity, and alignment with business intent
• Validate data outputs by comparing results against existing reports, source systems, and stakeholder expectations
• Collaborate with senior Analytics Engineers to learn and adopt modern analytics engineering practices and tooling
• Actively learn and ramp up on the modern data stack (including dbt and related tools), demonstrating curiosity and a fast-learning curve
• Communicate effectively with analytics, technical teams, and business consumers to ensure data solutions meet real business needs

• Develop and maintain ETL processes to support data ingestion, transformation, and integration.
• Work with various file formats (TXT, CSV, XML, JSON, YAML) to ensure seamless data processing.
• Implement and optimize ETL workflows using EasyMorph, Databricks, Azure Data Factory, Talend, and Apache Nifi.
• Write clean, efficient, and maintainable code using Python, C#, or Java.
• Ensure data quality, accuracy, and integrity across ETL pipelines.
• Collaborate with data engineers and analysts to define and refine ETL requirements.
• Troubleshoot and resolve ETL failures, ensuring minimal downtime and impact.
• Follow test-driven development (TDD) methodologies to improve reliability and maintainability.
• Maintain and document ETL processes, providing insights and recommendations for improvements.

Associate ETL Engineer

• Design and develop scalable data models that power our data products
• Collaborate with key stakeholders across product, engineering, operations, and data science teams
• Contribute to and improve our dbt implementation and data models
• Collaborate with partners across technical and non-technical teams
• Support key decision makers about the state of the business
• Participate in development, testing, documentation, and evangelism of core data models
• Utilize analytical tools like Databricks, BigQuery, Airflow, Mode, and Tableau

• Maintain and expand the company’s analytical data model using Snowflake and dbt, ensuring datasets are reliable, well-structured, and easy to use.
• Partner with stakeholders to understand reporting and analytics needs and translate them into new models and datasets.
• Investigate discrepancies in metrics and datasets and perform root-cause analysis across systems.
• Monitor and maintain ELT pipelines across our data stack.
• Investigate and resolve pipeline failures, schema changes, and data inconsistencies.
• Identify opportunities to improve pipeline reliability, efficiency, and cost effectiveness.
• Expand documentation across the data model to clearly describe business logic, relationships, and definitions.
• Ensure datasets are clearly structured and documented so they can be reliably used across analytics tools and internal workflows.
• Contribute to the structured AI data context files that help internal AI tools accurately interpret datasets and metrics.
• Help maintain data governance standards, including contributing to PII masking policies and ensuring sensitive customer data is handled appropriately across the data platform.
• Work closely with Product, Revenue, and Operations teams to understand their data needs and questions.
• Help stakeholders navigate the data model and identify the most appropriate datasets for their use cases.
• Occasionally build or modify Hex projects to support data exploration or reporting needs.

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Analytics Engineer

Senior ETL Developer

Analytics Engineer

Associate ETL Engineer

Analytics Engineer

Analytics Engineer