Engineering Jobs 2026 (Now Hiring) – Smart Auto Apply
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Lead I - Software Engineering
$58 - $58 / hour
Posted 4 days ago

Engineering Manager
$120,000 - $135,000 / year
Posted 30+ days ago
Engineering Technician (Starlink/Akoustis)
$22 - $43 / hour
Posted 30+ days ago

Cyber Defense & Engineering - Cloud Security Consultant, Director
$155,000 - $410,000 / year
Posted 30+ days ago

Engineering Manager, Tokenization
Posted 30+ days ago
Director Of Firmware Engineering - Embedded Systems/Pcie/Cxl/Nvme/Ethernet/Serial Interconnect
$190,280 - $285,000 / year
Posted 30+ days ago
Senior Manager, Infrastructure Engineering
$160,000 - $250,000 / year
Posted 30+ days ago
Engineering Manager- Technical Program Manager
$114,000 - $132,000 / year
Posted 30+ days ago
Civil Engineering Technician
Posted 30+ days ago
Manager Engineering
$118,500 - $180,000 / year
Posted 3 days ago
Director, Reliability Engineering
$172,000 - $297,850 / year
Posted 30+ days ago
Engineering Manager
$200,000 - $230,000 / year
Posted 30+ days ago
AI Quality Engineering Lead-Eden Prairie, MN (Hybrid)
Posted 3 days ago
Maintenance And Engineering Technician IV
Posted 1 week ago
Manager, Systems Engineering
$253,600 - $380,400 / year
Posted 30+ days ago
Sr Manager Software Engineering - Data Acquisition
$175,600 - $204,300 / year
Posted 30+ days ago
Senior Director - Software Engineering (Mulesoft) (Hybrid - Newark, NJ)
$165,000 - $175,000 / year
Posted 30+ days ago
Manager, R&D, Electrical Engineering
$121,000 - $171,000 / year
Posted 1 week ago
Staff Technical Solution Engineering
$153,400 - $210,850 / year
Posted 3 weeks ago
Staff Engineer Engineering Compute Infrastructure And Grid Operations
$128,000 - $189,370 / year
Posted 30+ days ago
Lead I - Software Engineering
$58 - $58 / hour
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Overview
Job Description
- Sr Engineer, Data designs and delivers scalable data architectures and advanced data engineering solutions across on-premises, cloud, and hybrid platforms to support enterprise analytics and customer intelligence use cases.
- This role partners closely with data engineers, architects, and analytics teams to analyze, design, and optimize data warehouse and analytics solutions that power personalization and data-driven decision-making within the customer data platform.
- The Sr Engineer provides hands-on technical leadership, mentors engineers, and drives the evolution of modern data architectures.
- Success is measured by solution effectiveness, scalability, performance, and growth in team capability and architectural maturity.
- Design and develop advanced data engineering solutions that enable data pipelines, visualization, and analytical tools
- Architect and implement scalable data platforms across on-premises, cloud, and hybrid environments
- Build, optimize, and operate complex batch and real-time and near real-time streaming data pipelines
- Build, optimize, and operate low-latency, sub-second APIs on highly scalable, fault-tolerant architectures.
- Design and maintain high-throughput data pipelines to support agentic AI workloads and real-time multi-agent MCP orchestration.
- Build and maintain enterprise-scale Graph Databases that power organizational knowledge graphs and connected data experiences.
- Perform data wrangling, exploration, and discovery across heterogeneous data sources to generate insights
- Lead development of large-scale data processing solutions using Databricks and Spark technologies
- Contribute to team knowledge sharing and advancement of data engineering standards and capabilities
- Mentor engineers to strengthen technical skills, delivery quality, and professional growth
- Support project definition activities including estimation, planning, and scoping in partnership with management What You ll Bring
- Bachelor s Degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience
- 8+ years of hands-on experience designing, building, and supporting data engineering solutions
- Strong experience developing and migrating data solutions across cloud platforms
- Demonstrated technical leadership and mentoring experience
- Strong analytical and problem-solving skills applied to complex data challenges
- Ability to manage multiple concurrent initiatives with strong organizational and prioritization
- Passion for learning and applying new data and platform technologies
- Core Data Engineering & Platforms
- Advanced experience designing and building complex data pipelines using Python and SQL
- Strong experience with cloud platforms and services, including Azure (Data Factory, Data Lake, Event Hub, Functions, Web Apps, Cosmos DB)
- Databricks with PySpark, Spark SQL, and Scala Spark, including cluster configuration, autoscaling, and performance optimization (e.g., Photon)
- Snowflake data warehousing, including schema design (star/snowflake), query optimization, and cost/performance tuning
- Expertise in SQL, NoSQL, and relational database design and development
- APIs, Streaming & Integration
- Proficiency designing and consuming RESTful APIs with secure authentication and authorization (OAuth 2.0, JWT, API keys)
- Experience using Postman and Swagger/OpenAPI for API testing, documentation, and validation
- Working knowledge of message queuing, stream processing, and highly scalable big-data data stores
- Engineering Practices
- Advanced knowledge of data pipeline development using Python and experience with languages such as SQL, DAX, Java, Scala, and/or Go
- Experience performing root-cause analysis and using technology to solve complex business problems
- Experience adopting AI-assisted development tools and building AI-powered agents or agentic workflows to automate engineering tasks, accelerate delivery, and enhance data platform capabilities
- Experience with NL-to-SQL query generation using Databricks Genie and Snowflake Cortex to enable natural language access to data assets
- Hands-on experience with Unity Catalog for data governance, fine-grained access control, and end-to-end data lineage
- Experience developing AI-assisted dbt models, including AI-generated transformation logic, automated documentation, and intelligent testing
- Familiarity with AI-powered data quality tools for automated profiling, anomaly detection, and pipeline observability Nice to Have
- Experience with Iceberg table design and optimization
- Experience with Unity Catalog governance and security
- Cloud platform certifications such as Azure Certified Solutions Architect, Azure Cloud Practitioner, or MCSA
- Experience contributing to enterprise data governance, security, or compliance initiatives
- Experience with ML feature platforms (e.g., Feast, Tecton, or Databricks Feature Store) and vector database engineering (e.g., Pinecone, Weaviate, pgvector)
- Experience designing and operating streaming AI pipelines and applying MLOps practices to data engineering workflows
- Exposure to end-to-end ML pipeline ownership and real-time AI inference plumbing in production environments
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