Senior Data Architect (Snowflake) – Market Research
New
T
TruelogicMarket research
Location: BogotaFull-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
Requirements
- 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 covering 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.
Responsibilities
- Design scalable core tables that transform raw event data into reliable, well-structured datasets.
- 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 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 formats such as Parquet.
- Administer Snowflake environments, including role-based 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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