Senior Data Architect (Snowflake)- Market Research

Role overview This hands-on Senior Data Architect role owns the design, modeling, ingestion, and optimization of a large-scale Snowflake and dbt platform supporting a market research business that delivers data, forecasts, benchmarks, and expert analysis across advertising, media, commerce, technology, healthcare, and financial services. The architect turns raw S3 files and event data into reliable core tables and dimensional marts, partners with software engineers, and drives correctness, performance, security, governance, and cost across production environments.

Responsibilities - Design and build scalable core tables that turn raw event data into well-structured datasets, and engineer incremental dbt models for billion-row tables using merge strategies, clustering, deduplication, microbatch processing, and idempotent reprocessing. - Implement identity-resolution solutions that handle merged identities, late-arriving data, and duplicate events. - Design fact and dimension marts and define approved datasets for BI developers, analysts, and data scientists. - Solve complex SQL challenges around performance, correctness, window functions, and semi-structured data. - Design reliable ingestion from Amazon S3 into Snowflake using Snowpipe, stages, storage integrations, COPY INTO, and schema evolution. - Partner with software engineers on event-driven delivery patterns, schemas, data contracts, and columnar formats such as Parquet. - Administer Snowflake environments, including RBAC, security policies, integrations, and warehouse configuration, and monitor pipeline stability, freshness, and failures. - Optimize Snowflake and dbt performance and cost, establish documentation standards, evaluate trade-offs, and review SQL, dbt, and Python code.

Requirements - 6+ years in data engineering, data architecture, or analytics engineering, including 3+ years of hands-on production Snowflake experience. - Expert-level SQL and advanced dimensional modeling, including fact and dimension marts, slowly changing dimensions, conformed dimensions, and semi-structured data. - Advanced dbt skills with incremental strategies, snapshots, macros, testing, and billion-row datasets. - Experience with behavioral or event data, including sessionization, identity resolution, late-arriving events, and duplicates. - Deep Snowflake expertise covering RBAC, Snowpipe, stages, storage integrations, COPY INTO, schema inference, tasks, streams, clustering, and cost management. - Working knowledge of AWS services such as S3, IAM, SNS, and SQS, plus experience designing event-driven integrations and formats such as Parquet, and the ability to read and review Python code. - Strong written and verbal English communication, with the ability to explain architectural trade-offs to engineers and business leaders, and a track record of taking complex data problems from diagnosis through production with minimal direction.

Benefits and work setup - 100% remote work with flexibility to manage time as long as results are delivered. - Highly competitive USD compensation, paid time off, and opportunities to contribute to high-impact projects with U.S. companies.