Data Engineer — Analytics & Migration Validation (Hands-On SQL)BuildingBlocks Software Services Pvt Ltd • Snowflake, Arizona, United States
Data Engineer — Analytics & Migration Validation (Hands-On SQL)
BuildingBlocks Software Services Pvt Ltd
- Snowflake, Arizona, United States
- Snowflake, Arizona, United States
À propos
Our way of life is more reason than work, mixing the quest for certified human association with a fastidious way to deal with the things we make. All with an idealistic soul. We’re an organization that is adequately youthful to be fun and defiant – yet intense and driven enough to immensely affect the business.
Role Overview We’re looking for a hands-on
Data Engineer
to own the data layer of customer go-lives — ensuring migrations are validated, analytics pipelines are hardened, and business dashboards are powered by accurate, performant data. You’ll be responsible for validating and signing off on end-to-end data migrations, building high-quality SQL models, and implementing automated data quality checks to catch issues early.
This is a highl technical and impact-driven role focused on
migration testing, SQL performance tuning, and data quality automation
— aligning with AWS and industry best practices.
Key Responsibilities
End-to-End Migration Validation:
Design and execute functional and performance validation for data migrations — including parity, nullability, PK/FK, duplication, and sampling checks — with complete documentation and sign-off aligned to AWS migration testing guidelines.
Advanced SQL Development:
Write and optimize analytical SQL (CTEs, window functions, incremental loads). Use EXPLAIN plans to tune query performance and ensure indexes and statistics support BI workloads.
Automated Data Quality Frameworks:
Implement and maintain data validation frameworks using
Great Expectations, Deequ,
or similar tools. Automate validation and publish Data Docs to ensure transparency across teams.
Modeling & Documentation (dbt):
If using dbt, build models with tests, exposures, and documentation to ensure traceability between dashboards and upstream data sources.
Orchestration & Reliability:
Productionize data validation and transformation jobs within
Airflow DAGs,
ensuring welldefined SLAs, alerts, and reliable pipeline operations.
(Optional) Cloud Data Engineering:
Build incremental pipelines and optimize batch processing for
Snowflake
(Streams & Tasks) or
PostgreSQL , ensuring performance and cost efficiency.
Minimum Qualifications
Experience:
4–7+ years as a Data Engineer or Analytics Engineer.
SQL Expertise:
Advanced proficiency in SQL and strong RDBMS fundamentals (PostgreSQL required), with proven experience in query tuning using EXPLAIN/analyze.
Migration Validation:
Hands-on experience designing and executing data migration validation (parity, integrity, and performance testing).
Tooling Knowledge:
Experience with one or more of the following —
dbt, Great Expectations or Deequ/PyDeequ, Airflow.
Version Control:
Comfortable with Git-based workflows and CI/CD integration.
Nice to Have
Experience with
Snowflake
(Streams, Tasks, cost optimization, and warehouse tuning).
Exposure to BI tools such as
Looker, Power BI, Tableau, or Metabase .
Working knowledge of
Python
for lightweight data transformations and validation frameworks.
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Compétences linguistiques
- English
Avis aux utilisateurs
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