A squad of specialists embedded to deliver projects, train your team and implement the data strategy your company needs — from the DBA to the data scientist, from diagnosis to operation.
From database administration to insights delivery — with senior professionals and proven enterprise-grade methodology.
Senior DBAs specialized in Oracle, SQL Server, PostgreSQL, MySQL, MongoDB, MariaDB and more. Tuning, high availability, replication, backup, upgrade, troubleshooting and 24×7 operation.
See supported engines →Analysis of slow queries, indexes, execution plans, partitioning and capacity planning. We solve bottlenecks others can't find.
Learn more →Pipelines, ETL/ELT, data lakes and data warehouses in cloud (AWS, Azure, GCP) or on-premises. Integration from any source to any destination.
Learn more →Executive dashboards, KPIs and reports in Power BI, Tableau, Qlik and Looker — with governance, security and dimensional modeling.
Learn more →Predictive models, clustering, time series, NLP and generative AI applied to real business cases.
Learn more →Design of scalable architectures, data mesh, lakehouse, modern data stack — engineered for your volume and complexity.
Learn more →Migration between engines (e.g., Oracle → PostgreSQL), on-premises to cloud, version upgrades and instance consolidation — without losing data.
Learn more →AI agents, <strong>N8N low-code</strong> flows, API integrations and classic RPA. Cognitive and operational automation with Python, Airflow and LLMs.
Learn more →Senior professionals embedded in your team — DBAs, Data Engineers, Analytics Engineers, BI Devs, Data Scientists, Architects and Tech Leads.
Learn more →Immersion in your context, source mapping, pain points and opportunities.
Detailed scope, timeline, team and investment — no surprises.
Bi-weekly sprints with incremental deliveries and continuous validation.
Sustainment, evolution and training of the internal team for autonomy.
End-to-end data platform modernization projects — from architecture to the first use case in production, with our WFSLib library that cuts development time by up to 70%.
Data lake implementation in bronze / silver / gold layers on ADLS Gen2 (Azure), S3 (AWS) or GCS (Google Cloud). Ingestion from any source — relational databases, NoSQL, APIs, files, streaming. Dimensional modeling, partitioning and cost optimization.
Big data platforms on Databricks, Microsoft Fabric, Snowflake, Synapse or BigQuery. Lakehouse with Delta Lake or Iceberg, unified governance, column-level lineage, petabyte-scale Spark processing and Time Travel.
Modern data architecture design: Modern Data Stack, Data Mesh, Medallion Architecture, Data Vault 2.0. Tool selection, cloud sizing, TCO and phased implementation roadmap.
Migration of on-premises data warehouses (Teradata, Netezza, Oracle) to cloud (Snowflake, BigQuery, Synapse). Stored procedure refactoring, data parity validation, zero-downtime cutover and internal team training.
Data catalog, dictionary, column-level lineage, business glossary and automatic PII map — using our own WFS Smart Document IA. Defensible compliance for LGPD, ISO 27001 and SOX.
Dedicated data engineering squad or professional staffing. Pipelines on PySpark, Airflow, dbt, Kafka, Flink. Data CI/CD, quality testing, observability and SRE tailored to the data platform.
Need a senior tomorrow? WFS places consultants and specialists into your team — onboarding within 5 business days, flexible contract, guaranteed backup on swaps.
Senior DBA on Oracle, SQL Server, PostgreSQL, MySQL, MongoDB, MariaDB, DB2, Cassandra, Redis. 24×7, on-call or business-hours model. Contractual SLA, NDA and backup during vacation/leave.
Mid and senior Data Engineer on PySpark, Airflow, dbt, Kafka, Delta Lake, cloud-native (AWS / Azure / GCP). Building resilient pipelines, observability and data SRE.
Data Scientist on supervised and unsupervised ML, time series, NLP, deep learning and MLOps. Focus on real business cases with measurable value delivery.
BI Developer / Analytics Engineer on Power BI, Tableau, Qlik, Looker, dbt. Advanced DAX/M, dimensional modeling, RLS, governance and business-area enablement.
Architect / Tech Lead for platform design, code review, technical mentoring, technology selection, cloud sizing and cost, and alignment with C-level stakeholders.
ML / AI Engineer specialized in generative AI, the leading LLMs on the international data market, RAG, agents, fine-tuning and MLOps. For applied AI initiatives and corporate copilots.
RPA Developer on UiPath, Power Automate, Selenium and N8N. Cognitive automation with LLM integration for cases involving OCR, classification and decision-making.
Data governance specialist, PII mapping, data classification, access control, retention policies and LGPD / ISO 27001 / SOX adequacy.
Closed multidisciplinary team: PO + Tech Lead + Engineers + BI + Data Scientist. Cell model, biweekly sprints, delivery metrics, ideal for modernization or new data product projects.
All profiles go through strict technical screening and cultural interview. Request profiles and we deliver a shortlist within 3 business days.
Request a free diagnosis and get a tailored proposal within 2 business days.
Request a quoteFixed project: scope, deadline and value defined in contract. WFS delivers the outcome regardless of effort — ideal for clear deliverables (DW implementation, database migration, executive dashboard). Consultant staffing: senior professionals placed in your team, under your day-to-day management, body-shop or dedicated-squad model. You pay hourly or monthly. Ideal for ongoing demand, sustainment or hybrid teams.
Varies with scope, seniority and duration. As reference: senior professional staffing has hourly rates aligned with SP/Curitiba data market; fixed-price data lake MVP implementation ranges from R$ 80k to R$ 250k depending on complexity; database tuning consulting is billed per 2-week sprint. Request a quote with your scenario and receive a tailored proposal within 2 business days.
For common profiles (SQL Server/Oracle DBA, PySpark Data Engineer, Power BI BI Developer), the shortlist comes within 3 business days and onboarding within 5 business days. Rare specialist profiles (senior generative AI, Databricks data architect with 10+ years) can take up to 15 business days. We keep an internal pool of pre-screened talents that accelerates the process.
Yes. AI and Data Science consulting covers: business problem discovery, data prep, modeling (regression, classification, time series, NLP, deep learning, generative AI), MLOps for production (model CI/CD, drift monitoring, A/B testing), and LLM applications in corporate cases (RAG, agents, copilots). We use the leading international LLMs on the data market and open-source models. Mid, senior and specialist teams.
We operate on Microsoft Azure (ADLS Gen2, Synapse, Fabric, Data Factory, Power BI), AWS (S3, EMR, Glue, Redshift, Athena, QuickSight), Google Cloud (BigQuery, Dataproc, Looker), Oracle Cloud Infrastructure (OCI) and on-premises environments (Hadoop, Cloudera, Databricks on-prem). Also hybrid and multi-cloud architectures.
Yes. We have connectors and know-how on TOTVS Protheus, TOTVS Datasul, Senior, SAP ECC and SAP S/4HANA, Oracle EBS. We do extraction to data warehouse, ERP-specific modeling, executive dashboards with KPIs adapted to the Brazilian business model (tax regime, NF-e, CFOP, chart of accounts) and integration with a cloud analytics layer.
All connections to production data are read-only by default. Credentials live in dedicated vaults (Azure Key Vault, AWS KMS, GCP Secret Manager or HashiCorp Vault), never in code. Automatic PII detection and masking (CPF, CNPJ, RG, email, card). AES-256 encryption at rest and TLS 1.3 in transit. Standard NDA, full access auditing and DPO reports. Compliant with LGPD, GDPR and SOX.
Yes. We recommend a 2-4 week Proof of Concept (PoC) with limited scope (1-2 data sources, 1 use case) to validate technical fit, delivery quality and expected ROI. Some PoCs are free (when commercial fit is clear); others are billed with credit toward the main contract. Talk to our sales team to align the model.