
51 - 200 employees
Founded 2008
🏢 Enterprise
Enterprise • Data
Mactores is a company that provides end-to-end data platform solutions aimed at accelerating business value through automation. Since 2008, Mactores has been helping businesses with digital transformation, offering services like Enterprise Data Lakes, Scalable Databases, Modern Data Warehouses, Automated DataOps, MLOps, and Generative AI solutions. They focus on enabling faster and cost-effective migrations and modernizations in data analytics, partnering with leading platforms to drive innovation and success. Mactores works alongside tech teams to strategize and implement the right data solutions timely and efficiently.
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51 - 200 employees
Founded 2008
🏢 Enterprise
Enterprise • Data
Mactores is a company that provides end-to-end data platform solutions aimed at accelerating business value through automation. Since 2008, Mactores has been helping businesses with digital transformation, offering services like Enterprise Data Lakes, Scalable Databases, Modern Data Warehouses, Automated DataOps, MLOps, and Generative AI solutions. They focus on enabling faster and cost-effective migrations and modernizations in data analytics, partnering with leading platforms to drive innovation and success. Mactores works alongside tech teams to strategize and implement the right data solutions timely and efficiently.
• Build extraction pipelines from SAP HANA to AWS S3 using SLT, ODP, CDS views, SDI, and native HANA SQLScript, picking the right tool per source and per latency requirement. • Model raw SAP tables across FI/CO, MM, SD, and adjacent modules into clean, semantically meaningful datasets that the downstream Spark layer and business users can actually use. • Design and operate delta and CDC patterns so incremental loads stay correct, idempotent, and replayable. • Write ABAP extractors where standard SAP tooling falls short, and document them so future engineers can change them safely. • Own the write-back path: load curated data from S3 into SAP BW / BW4HANA and model it for end-user reporting and analytical querying. • Land data in S3 as Parquet with sane partitioning, schemas, and IAM scoping, and define the contract with the PySpark engineer at the ingestion-to-transformation boundary. • Embed with a customer team, ship the pipeline to production, and stay close enough through cutover to know it actually runs.
• Deep SAP HANA extraction experience: real production work with SLT, ODP / operational data provisioning, CDS views, SDI, and HANA SQLScript. • Strong grasp of SAP table structures and the business semantics behind them in at least one functional area (FI/CO, MM, SD, or similar), so you can turn raw tables into models a business analyst recognizes. • Solid delta and CDC instincts: you've designed incremental loads that survive reprocessing, late-arriving data, and source-side schema drift. • ABAP fluency sufficient to build custom extractors when standard tooling can't reach the data. • SAP BW / BW4HANA data loading and modeling experience for the consumption side of the pipeline. • Working AWS knowledge: S3 landing zones, Parquet, basic IAM, enough to collaborate confidently on an AWS-hosted pipeline without needing to own the platform. • Strong written and spoken English. You'll be on customer calls and working across geographies. • Preferred: Have worked with AWS Glue Data Catalog or similar metadata layers over S3. • Have shipped SAP-to-cloud data lake patterns before, with opinions on what broke and how you'd do it differently. • Have done client-facing consulting or forward-deployed delivery, not just internal IT work.
• We care about creating a culture that makes a real difference in the lives of every Mactorian. • At Mactores, we are committed to providing equal opportunities in all of our employment practices.
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