Senior Data Engineer ID82547

AgileEngine; Brasília; Teletrabalho; BRL 180 000 - 320 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Growth without limits

Competitive compensation

Flexibility: 100% remote with flexible

Meaningful projects

Collaborative culture

Well-being & support

Resumo da oferta

AgileEngine is seeking a Senior Data Engineer to partner with an internal data team on a Customer Data Platform initiative, building Snowflake semantic structures, cleaning and transforming customer datasets, and developing AI-ready data models for a growing retail brand. You will write production-grade SQL and Python, build data models, and maintain rigorous technical documentation.

Eastern Time overlap preferred.

Qualificações

• 4+ years writing complex, optimized SQL with window functions
• Strong Python for data manipulation, automation, and data quality checks
• Cloud platform experience (AWS, Snowflake, GCP or Azure)
• Strong stakeholder communication and ability to translate needs into technical specifications
• Rigorous documentation habits and code comments
• Upper-intermediate English level

Responsabilidades

• CDP Data Modeling in Snowflake: clean, transform, and structure incoming datasets to feed the CDP
• AI readiness: develop Snowflake views, semantic models, and metadata for AI agents and BI tools
• Ad-hoc data prep for retail initiatives (inventory, RFID, customer analytics)
• Write production-grade SQL and Python for data transformation and wrangling
• Collaborate with stakeholders to translate business requests into data models
• Parse and flatten semi-structured data (JSON) from cloud sources
• Maintain data models and semantic views in Snowflake
• Create data dictionaries and documentation for assets
• Maintain Git workflows and data testing practices
• Support evolving analytics engineering priorities

Conhecimentos

SQL (advanced)

Python scripting

Stakeholder communication

Documentation discipline

English proficiency

Ferramentas

dbt

Snowflake

Airflow

Retail Analytics

Descrição da oferta de emprego

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a
Senior Data Engineer to partner with an internal data team on a Customer Data Platform initiative, building Snowflake semantic structures, cleaning and transforming customer and behavioral datasets, and developing AI-readiness data models for a growing retail brand. You will write production-grade SQL and Python, build and maintain data models and semantic views in Snowflake, collaborate directly with cross-functional business stakeholders to translate operational needs into technical specifications, and maintain rigorous technical documentation across all built assets. Eastern Time Zone overlap preferred.

WHAT YOU WILL DO

• CDP Data Modeling (Primary Focus): Partner with an internal data team member to clean, transform, and structure incoming customer, sales, and behavioral datasets inside Snowflake to feed the Customer Data Platform.
• AI Readiness & Semantic Layer: Assist in developing Snowflake views, semantic models, and structured metadata to ground downstream AI agents and BI tools (Sigma).
• Ad-Hoc Operational Data Prep: Work with cross-functional stakeholders to engineer datasets for key retail initiatives (e.g., store inventory/RFID data projects, customer analytics).
• Write production-grade, performant SQL queries and Python scripts for data transformation, extraction, and automated data wrangling.
• Partner directly with business stakeholders to translate ambiguous business requests into clean, structured data models.
• Parse and flatten complex semi-structured data (JSON, nested payloads) landed from cloud sources.
• Build and maintain data models and semantic views in Snowflake.
• Write thorough data dictionaries, model descriptions, and documentation for built assets.
• Maintain clean code repositories and follow git workflows and data testing protocols.
• Take on additional analytics engineering priorities as assigned, based on evolving business needs.

MUST HAVES

• 4+ years writing complex, optimized SQL — window functions, and handling semi-structured/nested data formats.
• Strong Python: Proficient writing clean, modular Python scripts for data manipulation, automation, API/file processing, and data quality checks.
• Cloud Platform Experience: Hands-on experience working within at least one major cloud data ecosystem (AWS, Snowflake, GCP, or Azure).
• Strong Stakeholder Communication: Ability to collaborate directly with business partners, ask clarifying questions, and turn operational needs into technical specifications.
• Rigorous Documentation Focus: A disciplined habit of maintaining thorough technical documentation and code comments.
• Upper-intermediate English level.

NICE TO HAVES

• dbt (Data Build Tool): Experience writing, modularizing, and testing dbt models.
• Snowflake & AWS S3: Direct experience querying Snowflake data warehouses and manipulating staging data stored in S3 buckets.
• Orchestration Tools: Familiarity with Apache Airflow or similar pipeline schedulers.
• Retail / E-Commerce Knowledge: Background in omni-channel retail, store operations, inventory management, or customer analytics.

PERKS AND BENEFITS

• Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
• Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
• Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
• Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
• Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
• Well-being & support: access local well-being programs and people-focused support tailored to your location