> Markdown version of [/jobs/ext/2636689-lead-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/2636689-lead-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). --- # Lead Analytics Engineer - **Company:** Sequoia Connect - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Query Performance, Amazon S3, Data Analysis, Confluence, JIRA, Automation of Tests, Collaborative Software, Data Architecture, Data Validation, Data Mapping, Data Presentation, Data Security, Identity and Access Management, Python (Programming Language), Oracle (Applications), Query Optimization, Simple Data Format, Amazon Simple Notification Service (SNS), SQL Databases, Tableau (Software), Parquet, GitHub Copilot, Statistics Packages, AWS Glue, Amazon Simple Queue Service (SQS), Software Version Control - **Published:** August 10, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eb9ad3fb59295aae ## About the Role * Expert-level proficiency in SQL on RDS, Oracle, and Redshift, including deep query tuning and vacuum/analyze awareness. * Proven expertise in AWS Athena, specifically regarding partitions, file formats, and cost control strategies. * Advanced Business Intelligence (BI) development skills with a strong emphasis on data storytelling and UX best practices for dashboards. * Strong Python programming skills focused on analysis, automation, packaging, and the reusability of common analytics functions (light use of pandas, statsmodels, scikit-learn). * Solid foundation in statistics tailored for inference and experiment design, with practical application in business contexts. * Demonstrated ability to translate complex business needs into robust analytical solutions using collaboration tools like Confluence and Jira. * High-Performance Mindset: Resilience, emotional intelligence, and a focus on agile delivery. * Technologist DNA: A deep understanding of the difference between "coding" and "engineering." Desired * Experience with advanced modeling tools and the governance of analytics layers. * Familiarity with AWS Glue Data Catalog, IAM basics for data access, and S3 file formats (Parquet/ORC). * Exposure to event-based data architectures (Kinesis, SNS, SQS) and data freshness SLAs. * Ability to build scalable, reusable dashboards and data models in QuickSight or Tableau while enforcing consistency and naming standards. * Familiarity with cloud-native foundations or AI coding assistants, such as GitHub Copilot or similar tools for code productivity. Languages * Advanced Oral English: For seamless collaboration with global teams. * Advanced Spanish., * Expert SQL on RDS/Oracle/Redshift (query tuning, vacuum/analyze awareness) and Athena (partitions, file formats, cost control). * Advanced BI development and data storytelling; strong UX best practices for dashboards. * Python for analysis and automation; packaging and reusability of common analytics functions. * Solid statistics for inference and experiment design; practical application in business contexts. * Collaboration tools (Confluence/Jira), stakeholder management, and ability to translate business needs into robust analytical solutions. ## Description * Deliver complex analytical work utilizing advanced SQL, focusing on performance tuning across RDS, Oracle, and Redshift, alongside cost-conscious querying in Athena. * Utilize Python to create reproducible analyses, automation scripts, and robust data validation checks. * Define data quality expectations, implement automated checks and anomaly detection, and triage resolutions collaboratively with engineering teams. * Conduct comprehensive deep-dive analyses, cohorting, funneling, forecasting, and experiment design. * Create and maintain Source-to-Target Mapping (STTM) documents through tight coordination with upstream and downstream stakeholders. * Improve query performance continuously through sort keys, distribution keys, partitioning, predicate pushdown, and compression awareness. * Establish strict version control and peer-review processes for analytics assets, contributing to lightweight CI for SQL and tests. ## Related Videos - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) - [Making Data Warehouses fast. 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