ArcTouch - Senior Backend Software Engineer (Data Engineering)

Remote - Brazil (Remote)1w ago

Remote Senior LATAM Cloud Computing Artificial Intelligence Data Engineer Software Engineer Contract Review C#.NET Python Azure GCP AWS Vault REST SQL GraphQL

Requirements

• Solid background in backend engineering, with proven experience in data engineering; • Strong C# / .NET and/or Python (PySpark a plus); • Hands-on experience with modern cloud data engineering platforms and tools (e.g., Microsoft Fabric — Data Factory, Dataflows Gen2, Lakehouse, OneLake, Notebooks — or equivalent services on Azure, AWS, or GCP); • Solid experience with cloud platform services (e.g., Azure Functions, SQL, Service Bus/Event Grid, Key Vault, or equivalents on other cloud providers); • REST APIs, GraphQL, webhooks, and event-driven integration patterns; • Experience integrating with SaaS platforms (PIM / eCommerce preferred); • Familiarity with Azure OpenAI or LLM-based pipelines; • SQL strong; graph query languages (GQL, Cypher, SPARQL) a plus. • Microsoft Fabric IQ (preview) experience; • Schema.org / JSON-LD familiarity; • CPG, retail, or eCommerce integration background; • Microsoft certifications: Azure or Fabric Data Engineer Associate. • REMOTE WORK: This position is remote-friendly. If you miss being in the office, we have a great one in Florianópolis and you are welcome to work from there whenever you wish. Just a reminder: remote employees must live in Brazil (we hire international professionals only for specific openings). • REMOTE WORK: • Just a reminder • Why work for us? Simple: We love what we do. • Make sure to check out our employee reviews on Glassdoor to find out why they love working for ArcTouch.

Responsibilities

• Inventory existing data sources (APIs, schemas, quality, schema markup); • Run gap analysis between current systems and the target Knowledge Graph model; • Support System Architecture design with integration and data-flow input; • Design ETL/ELT pipelines into the target lakehouse/data lake (e.g., OneLake), using tools such as Fabric Data Factory and Dataflows Gen2, or equivalent; • Design the LLM enrichment pipeline and human-review workflow; • Document API contracts, source-to-target mappings, and pipeline sequencing for Build.