Data Engineer
Sleek is looking for a skilled Data Engineer to join their growing Data Platform team. The ideal candidate will design, build, and maintain robust data pipelines on Databricks and AWS infrastructure, and have experience with ETL/ELT design patterns, ingestion patterns, and database internals. Requirements 3+ years of professional experience in data engineering Strong understanding of data platform architecture: Lakehouse, Data Warehouse, Data Lake patterns Hands-on experience with ETL/ELT design patterns including batch processing and stream processing Familiarity with ingestion patterns: full load, incremental, CDC, event-driven Strong understanding of database internals — storage engines, transactions, isolation levels, locking, MVCC, query planners Proven experience supporting mission-critical OLTP workloads with high availability requirements Solid scripting skills in Bash and/or Python for automation Experience building data pipelines on Databricks (Delta Live Tables, Jobs, Noteb
Data ScienceData EngineerDataOps Engineer Jobs
[ISO] Data Architect
Project – the aim you’ll have Define and govern the end-to-end data architecture that enables a scalable, secure, and business-aligned data platform — ensuring that data engineering, analytics, ML, and API initiatives are built on a coherent, future-proof foundation. Position – how you’ll contribute Define and own the end-to-end data architecture across lake, warehouse, and real-time streaming layers Establish architectural standards, design patterns, and best practices for all data domains Lead technology evaluation and selection for the cloud-native data platform stack Drive the long-term platform roadmap, including AI/ML readiness and data monetisation capabilities Design metadata management, data lineage, and access control frameworks in line with governance requirements Embed privacy-by-design, security, and compliance (including GDPR) at the architectural level Act as technical authority and design partner for Data Engineers, Data Scientists, and ML Engineers Represent data arch
Data ArchitectureData EngineeringData Platform Engineering
Machine Learning Engineer
Join Hire Hangar and work with fast-growing global companies while building a long-term, remote career. Machine Learning Engineer (Data & AI) Remote US Time Zones (EST–PST) Role Overview We are looking for a skilled Machine Learning Engineer with a strong data engineering foundation to build, train, and deploy ML models and data pipelines across a range of complex environments. This role sits at the intersection of data and AI — you will be responsible for everything from sourcing, cleaning, and structuring data to training models, evaluating performance, and getting solutions into production. The ideal candidate thinks rigorously about data quality, understands the full ML lifecycle, and is equally comfortable working with large datasets as they are fine-tuning models or building scalable inference pipelines. Key Responsibilities Design, build, and maintain robust data pipelines for ingestion, transformation, and feature engineering Develop, train, evaluate, and iterate on machin
Data ScienceMachine Learning EngineerAI Machine Learning Engineer
Argentina, Belize, Colombia, Dominican Republic, Honduras, Mexico, Nicaragua, Panama, Peru Data Quality Engineer
What is this position about? We are looking for a Data Quality Engineer with strong experience in Azure and Databricks to ensure data quality, reliability, and consistency across modern data platforms. This role focuses on validating data pipelines, implementing automated quality checks, and collaborating closely with Data Engineering and business teams to guarantee accurate and production-ready data assets. Design and implement a data quality framework across Bronze, Silver, and Gold layers — defining validation rules, threshold tolerances, and alerting standards Build and maintain automated data quality checks within Databricks pipelines — row counts, null checks, referential integrity, schema validation, and business rule assertions Own reconciliation between source systems and Databricks layers — ensuring source data lands accurately and transformations produce expected outputs Validate identity resolution outputs in the Silver layer — reviewing match rates, investigating false po
Data Quality EngineeringData EngineeringData Quality Assurance
Senior Data Engineer – Cloud Data Products & Analytic Enablement
Company : Highmark Health Job Description : JOB SUMMARY ***CANDIDATE MUST BE US Citizen (due to contractual/access requirements)*** As a Senior Data Engineer – Cloud Data Products & Analytic Enablement, you will be instrumental in transforming diverse data sources into actionable intelligence, empowering critical business decisions across our organization and within our application ecosystem. This pivotal role demands a strong foundation in data engineering principles, combined with a keen focus on analytical engineering to unlock the full potential of our data assets. You will leverage your deep expertise in Google Cloud Platform (GCP) technologies, including Managed Airflow (Cloud Composer), BigQuery, Cloud Run Functions, DataFlow, DataProc, and DataPlex, to design, build, and optimize scalable data pipelines. Your work will encompass the entire data lifecycle from ingestion and processing to modeling and orchestration, ensuring the highest standards of data quality, performance
Senior Data EngineerCloud Data EngineerData Engineering
Manager, Data Analytics - Remote
This role is contingent upon a contract award. ICF is seeking an experienced Data Analytics Manager to lead enterprise data, analytics, governance, and AI-enabled capabilities for a complex federal technology services program. This role will support the design, implementation, and sustainment of data policy, standards, governance processes, portfolio management practices, data architecture, data quality controls, analytics products, dashboards, and secure data access models. The ideal candidate has demonstrated experience leading enterprise data initiatives in regulated environments, with strong technical credibility across data governance, data architecture, data engineering, analytics, data quality, metadata management, and responsible AI-enabled analytics. This role requires the ability to translate business, operational, and mission needs into governed, secure, and usable data capabilities that support decision-making, performance management, and continuous improvement. Job Locati
Data & AnalyticsData GovernanceEnterprise Data Management