Note: The job is a remote job and is open to candidates in USA. Sequoia Connect is a talent-first technology ecosystem connecting elite professionals with high-impact digital transformation projects through a global automation and cloud solutions partner. The Lead Analytics Engineer will lead KPI and semantic-layer governance, deliver advanced analytics using SQL and Python, improve cloud data warehouse performance, and establish data quality, version control, and peer-review practices.
Responsibilities
- Lead the design and governance of core KPIs, metric definitions, and semantic layers for Our Client
- 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
Skills
- Degree holders for the visa application process
- 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.'
- Advanced Oral English: For seamless collaboration with global teams
- Advanced Spanish
- 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
Benefits
- Eligible for the visa application process.
- Continuous learning and radical ownership.
- Exposure to complex engineering challenges through collaboration within an international network of expertise across 39 delivery centers worldwide.
- Remote work arrangement.
- Flexibility to support your lifestyle.
Company Overview