Analytics Engineer

We have an opening for an Analytics Engineer who 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.

Responsibilities

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

Requirements

2+ 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); Proficiency in programming languages such as Python or R; Familiarity with cloud data warehousing solutions (e.g., Snowflake, BigQuery, Redshift); Strong problem-solving skills and attention to detail; Excellent communication and collaboration skills

Nice to have

DBT - Preferred; Experience with Snowflake; Knowledge of data visualization tools (e.g., Tableau, Looker, Power BI); Experience with Finance domain/analytics; 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

Benefits

Health and welfare benefits; Paid leave; Generous paid time off policy; Competitive benefits package; Professional development opportunities; Educational opportunities; Career growth opportunities; Hybrid work model