Data Architect, Hands-On, Data Specialist

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🕒 June 26

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SysMap Solutions

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1999

SysMap Solutions is a services company devoted to offering technological development to its customers since 1997.

📋 Description

• Design, define and evolve enterprise data architectures, establishing standards, best practices and strategies that ensure scalability, performance, resilience, security and cost efficiency; • Work on the end-to-end design of data solutions, from understanding business needs with stakeholders to defining the technical architecture, ensuring compliance with functional and non-functional requirements; • Design analytical data models and consumption architectures, including dimensional modeling, definition of facts and dimensions, star schema, curation layers and structures for analytics and BI; • Define data storage and processing strategies for Data Lake, Data Warehouse, Lakehouse and Data Mesh environments, considering volume, latency, governance and cost; • Create and evolve ingestion, transformation and data delivery pipelines with a focus on resilience, scalability, observability and automation; • Apply DataOps and FinOps practices, promoting operational efficiency, continuous monitoring, data quality and optimization of cloud resource usage; • Ensure integration between data platforms and AI initiatives, supporting advanced analytics, Machine Learning and GenAI use cases; • Define standards for modeling, catalog, lineage, quality and data governance, ensuring consistency and reliability of information; • Support technical teams and business areas in translating business rules into analytical structures, metrics, KPIs, indicators and sustainable data models; • Serve as a technical reference, providing mentorship, architecture reviews and guidance on best practices to the data engineering team.

🎯 Requirements

• Solid experience in data engineering in medium- and large-scale environments; • Strong background in data architecture and analytical solution design; • Dimensional modeling; • Definition of fact and dimension tables; • Modeling for Data Warehouses, Data Marts and Lakehouse environments; • Experience with medallion data layers (Raw/Bronze, Trusted/Silver, Curated/Gold); • Organizing data for analytical and operational consumption; • Expertise in Big Data and distributed processing (especially Apache Spark); • Advanced SQL knowledge (query tuning and optimization for complex queries); • Advanced programming in Python and PySpark; • Experience with AWS services (Glue, EMR, Lake Formation, Redshift, S3, Step Functions, among others); • Experience with ETL/ELT pipelines (dbt, Glue); • Orchestration with Airflow and/or Step Functions; • Data integration via APIs, microservices and containers; • Experience with messaging systems (Kafka, Kinesis); • Knowledge of governance, security, compliance and access control; • Experience with observability and data quality (monitoring, auditing, traceability and lineage); • Code versioning, CI/CD, automated testing and code reviews; • Ability to translate business concepts into metrics, KPIs and OKRs; • Experience in technical leadership, mentoring and team development; • Experience in AI environments (data preparation for Machine Learning and GenAI); • Experience with Data Mesh, domain-oriented architecture and data products; • Knowledge of data catalogs, data lineage, data quality frameworks and federated governance; • Experience with data modeling for the financial sector.

🏖️ Benefits

• Not specified.