Informatica lead

Quantum Technologies. LLC; Chicago, Northern (IL, KY); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Equal opportunity employer

Job summary

Quantum Technologies LLC seeks a senior Data Engineer to lead the Informatica-to-dbt migration on Snowflake within Azure. You will architect modular data models (staging, core, mart), enforce naming conventions, and optimize performance across pipelines.

The role includes hands-on development, testing, and end-to-end validation to ensure parity with legacy outputs. Responsibilities include migration strategy, repository craftsmanship, and establishing robust CI/CD and data quality checks in

Qualifications

• 8+ years total experience in Data Engineering / ETL / Data Warehousing.
• 3+ years hands-on experience with dbt (Core or Cloud) building production-grade pipelines.
• Proven experience leading an Informatica dbt migration to Snowflake on Azure (or similar large-scale ETL modernization).
• Strong Snowflake experience: designing and developing schemas, views, warehouses, and performance optimization.
• Solid working knowledge of Azure data stack: Azure Data Factory, ADLS, Azure DevOps/GitHub.

Responsibilities

• Define the target ELT architecture using dbt on Snowflake, integrated with Azure services (ADF, ADLS, Synapse/Databricks, Key Vault, Azure DevOps/GitHub).
• Translate legacy Informatica mappings, workflows, and sessions into modular dbt models (staging, core, mart layers).
• Establish modeling standards (naming conventions, layer design, folder/package structure) for staging, integration, and mart layers.
• Define and implement performance-optimized patterns in dbt and Snowflake (incremental models, clustering, partitioning logic, query tuning).
• Lead the migration strategy, roadmap, and wave planning for converting Informatica jobs to dbt on Snowflake.
• Analyze existing ETL logic, dependencies, and schedules in Informatica and design equivalent or improved logic in dbt.
• Design a repeatable migration factory: templates, accelerators, mapping spreadsheets, and conversion playbooks for Informatica dbt.
• Oversee conversion, unit testing, and parallel runs to validate that dbt models match legacy outputs (row counts, aggregates, business rules).
• Lead hands-on development of dbt models, seeds, snapshots, tests, macros, and documentation.
• Define and implement testing strategy using dbt tests (schema tests, data tests, custom tests) and integrate with broader data quality checks.
• Set up and maintain dbt environments (dev/test/prod), profiles, and connections to Snowflake on Azure.
• Introduce and enforce code quality practices.
• Code reviews & pull requests.
• Modular, reusable models and packages.

Skills

Data engineering

ETL / Data warehousing

dbt (Core or Cloud)

Informatica migration experience

Snowflake optimization

Azure stack experience

Leadership / migration project

Education

Bachelor's degree in a related field

Tools

dbt Core/Cloud

Snowflake

Azure Data Factory

Azure Data Lake Storage (ADLS)

Azure DevOps / GitHub

Job description

• Define the target ELT architecture using dbt on Snowflake, integrated with Azure services (ADF, ADLS, Synapse/Databricks, Key Vault, Azure DevOps/GitHub).
• Translate legacy Informatica mappings, workflows, and sessions into modular dbt models (staging, core, mart layers).
• Establish modeling standards (naming conventions, layer design, folder/package structure) for staging, integration, and mart layers.
• Define and implement performance-optimized patterns in dbt and Snowflake (incremental models, clustering, partitioning logic, query tuning).
• Lead the migration strategy, roadmap, and wave planning for converting Informatica jobs to dbt on Snowflake.
• Analyze existing ETL logic, dependencies, and schedules in Informatica and design equivalent or improved logic in dbt.
• Design a repeatable migration factory: templates, accelerators, mapping spreadsheets, and conversion playbooks for Informatica dbt.
• Oversee conversion, unit testing, and parallel runs to validate that dbt models match legacy outputs (row counts, aggregates, business rules).
• Lead hands-on development of dbt models, seeds, snapshots, tests, macros, and documentation.
• Define and implement testing strategy using dbt tests (schema tests, data tests, custom tests) and integrate with broader data quality checks.
• Set up and maintain dbt environments (dev/test/prod), profiles, and connections to Snowflake on Azure.
• Introduce and enforce code quality practices.
• Code reviews & pull requests.
• Modular, reusable models and packages.

Minimum Skills Required:

• 8+ years total experience in Data Engineering / ETL / Data Warehousing.
• 3+ years hands-on experience with dbt (Core or Cloud) building production-grade pipelines.
• Proven experience leading an Informatica dbt migration to Snowflake on Azure (or similar large-scale ETL modernization).
• Strong Snowflake experience: designing and developing schemas, views, warehouses, and performance optimization.
• Solid working knowledge of Azure data stack: Azure Data Factory, ADLS, Azure DevOps/GitHub.

QUANTUM TECHNOLOGIES LLC is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. QUANTUM TECHNOLOGIES LLC will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will QUANTUM TECHNOLOGIES LLC require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract