Engineering manager, data science engineering

hace 1 día

Chihuahua City, México The Ksquare Group A tiempo completo

About UsThe Ksquare Group was established in 2014 in Dallas TX, we are an international company with a presence in different countries such as Mexico, the USA, India, and Dominican Republic currently being more than 250 Ksquarians and growing. Depending on the skills required by every project, the best professionals are selected to bring all their talent together to achieve mutual goals. We are looking for a senior technical leader and hands-on architect — a Principal Data Engineer — to own the design and evolution of an AWS + Databricks enterprise lakehouse spanning ingestion (batch/streaming), transformation (canonical/Silver), and curated insights (Gold), with strong governance, security, performance, and cost controls. This role sets engineering standards, mentors teams, and drives scalable delivery across multiple domains and source systems.Raw landing on S3 + Glue CatalogDefine standards for data layout, partitioning, file sizing, compaction, and Iceberg table management.Establish platform patterns for batch + streaming ingestion, orchestration, and automated deployment.Data Engineering Delivery (Hands-On + Leadership)Lead implementation of scalable pipelines in Databricks (Py Spark/Spark SQL) and AWS (Glue, Lambda, Step Functions where needed).Design and maintain robust data models (canonical/Silver) and curated marts (Gold) optimized for analytics and downstream use.Kafka/Kinesis patterns if applicable, structured streaming/micro-batch).Ensure correctness, idempotency, late arriving data handling, and replay strategies.IAM, least privilege, encryption (KMS), secrets management, network controls.Establish data access patterns including RBAC/ABAC and controlled data sharing with partners.Performance, Reliability & Fin OpsDrive optimization on Databricks clusters, job tuning, caching strategies, and query performance.Engineering Excellence & Team EnablementCreate reference architectures, coding standards, reusable libraries, and delivery playbooks.Mentor data engineers and reviewers; Collaborate with stakeholders across Analytics/BI, AI/ML, and product teams.15+ years in Data Engineering with proven leadership owning enterprise-scale platforms.~ Spark architecture, Py Spark optimization, Spark SQL, workflows, job orchestration, cluster policies.~ Deep AWS expertise: S3, Glue, Lake Formation (if used), IAM, Cloud Watch, KMS, VPC/security controls.~ Iceberg (preferred) / Delta / Hudi and parquet optimization.~ Strong architecture skills for data ingestion, canonical modeling, and curated layer design.~ Strong hands-on coding in Python and advanced SQL.~ Experience implementing CI/CD for data (Git branching, deployment automation, environment promotion).~ Experience designing for analytics consumption: semantic layer readiness, BI/Power BI integration patterns.Experience with Unity Catalog, multi-workspace governance, data sharing, and fine-grained access controls.Exposure to data virtualization patterns (semantic/virtualization layer) and federation strategies.AI/ML enablement experience (feature datasets, training data pipelines, governance for Gen AI/LLM apps).Experience integrating enterprise apps (ERP, Service Now, Workday, factory systems like MES).

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