> Markdown version of [/jobs/ext/1791886-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/1791886-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Constant Contact - **Location:** Waltham, MA, United States (Remote available) - **Experience:** Starter - **Salary:** $84,800.0 - $101,760.0 - **Contract:** Permanent contract - **Skills:** Airflow, Data Analysis, BigQuery, Cloud Database, Computer Programming, Data Validation, Information Engineering, Data Files, Data Governance, Extract Transform Load (ETL), Data Systems, Data Visualization, Python (Programming Language), Machine Learning, Power BI, SQL Databases, Tableau (Software), Snowflake, Information Technology, Tools for Reporting, Data Delivery, Looker Analytics, Data Pipelines, Amazon Redshift - **Published:** July 18, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17632237?backUrl=%2Fcareer%2F17632237%2FAnalytics-Engineer-Massachusetts-Waltham ## About the Role * Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field. A Master's degree is a plus. * 1-3 years of experience as an Analytics Engineer, Data Engineer, or a similar role. * Strong proficiency in SQL and experience with data modeling and schema design such as star and snowflake. * Experience with ELT tools and data pipeline frameworks (e.g., Apache Airflow, dbt, Fivetran).DBT - Preferred. * Proficiency in programming languages such as Python or R. * Familiarity with cloud data warehousing solutions (e.g., Snowflake, BigQuery, Redshift). Experience with Snowflake is desirable. * Knowledge of data visualization tools (e.g., Tableau, Looker, Power BI) is a plus. * Strong problem-solving skills and attention to detail. * Excellent communication and collaboration skills. Preferred Skills: * Experience with cloud databases * Experience in Reporting tools. * Knowledge of machine learning concepts * Familiarity with data governance and compliance standards. * Ability to work in an agile environment. ## Description Job Summary: As an Analytics Engineer, you will bridge the gap between data analysis and data engineering. You will be responsible for transforming raw data into clean, reliable data sets, building robust data models, and enabling data analysts and other stakeholders to extract meaningful insights. Your work will directly impact decision-making processes across the organization., * Design, build and optimize data models for analytical and operational use cases. * Design, develop, and maintain scalable data pipelines and ELT processes to transform raw data into usable formats(as needed). * Collaborate with data analysts, data scientists, data engineers and other stakeholders to understand data needs and deliver high-quality, reliable data solutions. * Ensure data quality and integrity by implementing best practices for data validation, testing, and documentation. * Develop and maintain data infrastructure and tooling to support analytics workflows. * Monitor and troubleshoot data pipelines/models and reports to ensure smooth operation and timely data delivery. * Implement and enforce data governance and security measures. * Provide reliable and trustworthy models for the Organization to make critical decisions. * Experience with the Finance domain/analytics is a plus. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [Making Data Warehouses fast. 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