Senior Data Architect (Snowflake) - Market Research

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TruelogicMarket research

Location: LatAm; Workplace: RemoteFull-TimeSenior

Salary not disclosed

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Job Details

Languages: Strong written and verbal English communication skills.
Experience: 6+ years of experience in Data Engineering, Data Architecture, or Analytics Engineering; 3+ years of hands-on experience building production solutions with Snowflake.
Required Skills: AWSPythonSQLSnowflakeData modelingdbt

Have 6+ years of experience in Data Engineering, Data Architecture, or Analytics Engineering.
Have 3+ years of hands-on experience building production solutions with Snowflake.
Demonstrate expert-level SQL skills and ability to solve complex modeling, performance, and data-correctness problems independently.
Bring advanced data-modeling experience, including dimensional modeling, fact and dimension marts, slowly changing dimensions, conformed dimensions, and semi-structured data.
Have advanced dbt experience with incremental strategies, snapshots, macros, testing, and billion-row datasets.
Have experience with behavioral or event data, including sessionization, identity resolution, late-arriving events, and duplicates.
Bring deep Snowflake expertise, including RBAC, Snowpipe, stages, storage integrations, COPY INTO, schema inference, tasks, streams, clustering, and cost management.
Have working knowledge of AWS services, including S3, IAM, SNS, and SQS.
Have experience designing event-driven data integrations and working with formats such as Parquet.
Be able to read and review Python code.
Be able to take complex data problems from diagnosis through production with minimal direction.
Have strong written and verbal English communication skills and be able to explain architectural decisions and technical trade-offs to engineers and business leaders.

Design and build scalable core tables that transform raw event data into reliable datasets.
Engineer incremental dbt models for large tables using merge strategies, clustering, deduplication, microbatch processing, and idempotent reprocessing.
Implement identity-resolution solutions for 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 involving performance, correctness, window functions, and semi-structured data.
Design 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 access control, security policies, integrations, and warehouse configuration.
Monitor pipeline stability, load failures, data freshness, late-arriving events, and duplicate files.
Optimize Snowflake and dbt performance and cost, establish modeling standards, review code, document designs, and coach engineers and analysts.

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