Senior Data Engineer

Resolve Tech Solutions

Irving, Texas, United States

Irving, Texas, United States

À propos

We are seeking a Lead Snowflake Engineer to design, build, and operate robust data pipeline infrastructure that ingests from diverse source systems, normalizes data into consumption-ready models in Snowflake, and delivers clean, reliable datasets for Power BI reporting. This role is the connective tissue between raw data sources and business intelligence — you will own the full pipeline lifecycle from source connectivity through to report-ready data layers.
Core Responsibilities
Pipeline architecture & delivery — Design and implement end-to-end ELT pipelines that pull from all required source systems (APIs, relational databases, SaaS platforms, event streams) and deliver normalized, Power BI-ready data models in Snowflake.
Snowflake engineering — Architect schemas (star/snowflake/dimensional), write performant SQL, manage roles and warehouse sizing, and implement change management and data versioning practices.
Data normalization — Transform raw, heterogeneous source data into clean, consistent, consumption-ready layers purpose-built for Power BI semantic models and direct query patterns.
Source connectivity — Build and maintain reliable connectors to diverse upstream systems using REST APIs, database drivers, and cloud data services; handle authentication, pagination, retry logic, and error recovery.
Power BI optimization — Structure Snowflake data layers (fact/dimension tables, aggregations, pre‑computed metrics) to maximize Power BI report performance and developer productivity.
AI‑enhanced workflows — Leverage Snowflake Cortex and AI agent frameworks to build intelligent data products and automate analytical and data quality workflows.
Data quality & observability — Implement testing, monitoring, and alerting frameworks to ensure pipeline reliability and downstream data trustworthiness.
Required Skills
Snowflake (Expert):
Snowflake —
Hands‑on production experience designing schemas, writing advanced SQL (PIVOT, GROUPING SETS, ROLLUP/CUBE), managing Snowflake environments, warehouse sizing, and cost governance.
Proven ability to build normalized transformation pipelines that produce clean, consumption‑ready dimensional models from heterogeneous upstream sources.
Multi‑Source Integration:
Track record connecting and ingesting from relational databases, REST APIs, SaaS platforms, and event streams. Strong grasp of source‑specific extraction patterns.
Power BI Alignment:
Ability to design Snowflake data layers optimized for Power BI — fact/dimension structures, aggregation tables, calculated columns vs. measures trade‑offs, and DirectQuery performance.
Python:
Strong proficiency for data engineering tasks: pipeline orchestration, data transformation, API clients, scripting automation, and custom connector development.
AI Agents in Snowflake:
Familiarity with Snowflake Cortex, LLM functions, and agent‑based patterns for intelligent, data‑driven automation inside the Snowflake ecosystem.
Additional Skills
PostgreSQL & relational databases — Query optimization, indexing, and schema design patterns.
Cloud data infrastructure — Azure Data Factory, Event Hubs, AWS S3, or equivalent as source or orchestration layers.
dbt — Transformation layer experience with models, tests, documentation, and lineage tracking strongly preferred.
Data observability & testing — Experience with dbt tests, Great Expectations, Monte Carlo, or equivalent quality frameworks.
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Irving, Texas, United States

Compétences linguistiques

English

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