Senior Data Analytics Engineer

Summary

Join Tide's growing team as a Data Analytics Engineer and build and maintain data pipelines and services supporting marketing, business functions, reporting, and decision-making. You will work with BigQuery/Snowflake, Airflow, Stitch/Fivetran, dbt, and Tableau/Looker within an AWS/GCP environment. Responsibilities include developing ETL/ELT pipelines, designing scalable data processes, translating business requirements into technical specifications, troubleshooting, and improving data delivery. You will also perform data analysis, optimize data feeds, and champion data warehouse governance. Tide offers a flexible workplace model supporting both in-person and remote work.

Requirements

• Have 6+ years of extensive development experience using Snowflake or similar data warehouse technology
• Have working experience with dbt and other technologies of the modern data stack, such as Snowflake, Apache Airflow, Fivetran, AWS, git, Looker
• Have experience in agile processes, such as SCRUM
• Have extensive experience in writing advanced SQL statements and performance tuning them
• Have experience in Data Ingestion techniques using custom or SAAS tools like Fivetran
• Have experience in data modeling and can optimize existing/new data models
• Have experience in data mining, data warehouse solutions, and ETL, and using databases in a business environment with large-scale, complex datasets
• Have experience working in an agile cross-functional delivery team
• Have high development standards, especially for code quality, code reviews, unit testing, continuous integration, and deployment
• Have strong technical documentation skills and the ability to be clear and precise with business users
• Have business-level English and good communication skills

Responsibilities

• Develop end-to-end ETL/ELT pipelines working with Data Analysts of business functions
• Design, develop, and implement scalable, automated processes for data extraction, processing, and analysis in a Data Mesh architecture
• Translate business requirements into technical requirements, such as entities that need to be modeled, DBT models that need to be built, timings, tests, and reports
• Provide on-the-ground troubleshooting and diagnosis to architecture and design challenges and resolve technical issues as they arise
• Look for ways of improving both what and how data pipelines are delivered by the department
• Own the delivery of data models and reports end-to-end
• Perform exploratory data analysis to identify data quality issues early in the process and implement tests to prevent them in the future
• Work with Data Analysts to ensure that all data feeds are optimized and available at the required times. This can include Change Capture, Change Data Control, and other “delta loading” approaches
• Discover, transform, test, deploy, and document data sources
• Apply, help define, and champion data warehouse governance: data quality, testing, coding best practices, and peer review
• Build Looker Dashboards for use cases if required

Preferred Qualifications

• Have experience with Python, governance tools (e.g., Atlan, Alation, Collibra), or data quality tools (e.g., Great Expectations, Monte Carlo, Soda)
• Have experience with marketing attribution and Media Mix Modeling
• Have experience working in regulated industries
• Have a basic understanding of various systems across the AWS platform
• Have worked in a digitally native company, ideally fintech

Benefits

Flexible workplace model supporting both in-person and remote work