Infrastructure Engineer (Data & Automations) Job at ElevenLabs

Senior Solutions Engineer – Big Data & Data Infrastructure

This is a great opportunity to be part of one of the fastest-growing infrastruct...

Location

Israel , Tel Aviv

Salary:

Not provided

VAST Data

Expiration Date

Until further notice

Requirements

2–4 years in software / solution or infrastructure engineering
2–4 years focused on building / maintaining large-scale data pipelines / storage & database solutions
Proficiency in Trino, Spark (Structured Streaming & batch) and solid working knowledge of Apache Kafka
Coding background in Python (must-have)
Deep understanding of data storage architectures including SQL, NoSQL, and HDFS
Solid grasp of DevOps practices, including containerization (Docker), orchestration (Kubernetes), and infrastructure provisioning (Terraform)
Experience with distributed systems, stream processing, and event-driven architecture
Hands-on familiarity with benchmarking and performance profiling for storage systems, databases, and analytics engines
Excellent communication skills

Job Responsibility

Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools
Implement event-driven and serverless workflows
Create technical guides, architecture docs, and demo pipelines
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark)
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads
Operate and debug object store–backed data lake infrastructure

Staff Data Engineer - Vehicle Telemetry and Data Infrastructure

We are looking for a Staff Data Engineer to own the telemetry data platform for ...

Location

United States , Palo Alto

Salary:

230000.00 - 250000.00 USD / Year

ALSO

Expiration Date

Until further notice

Requirements

10+ years of experience in data engineering and/or backend platform engineering operating production systems at scale
Deep hands-on experience with large-scale telemetry or IoT data, including high-throughput and low-latency ingestion
Strong expertise in AWS data and infrastructure services (S3, Kinesis/MSK, Glue, EMR, Lambda, Step Functions, EventBridge)
Proven experience owning end-to-end ETL/ELT infrastructure using Spark/PySpark (batch and streaming) on Databricks or EMR
Solid understanding of streaming architectures using Kafka or equivalent systems and time-series–optimized storage patterns
Strong backend engineering skills using Python and/or Java/Scala, including API design (REST/gRPC) and distributed systems fundamentals
Experience with data platform architectures such as data lakes and lakehouses, schema registries, and metadata systems
Hands-on experience with orchestration frameworks (Airflow, MWAA, Dagster) and production-grade observability (logging, metrics, tracing)
Infrastructure-as-code expertise using CloudFormation, Terraform, or CDK to manage scalable and reliable systems
A track record of building highly reliable, fault-tolerant systems with clear ownership, strong SLAs, and operational excellence

Job Responsibility

Design and own large-scale ingestion pipelines for vehicle telemetry data (events, metrics, time-series) with high throughput and low latency
Architect and operate end-to-end ETL/ELT systems from raw ingestion to warehouse/lake consumption
Define schema evolution, versioning, and backward-compatibility strategies for telemetry data at scale
Build safe and repeatable backfill, replay, and reprocessing mechanisms for historical and real-time data
Design data storage and lifecycle strategies across hot, warm, and cold paths to balance cost and performance
Develop fault-tolerant, observable, and debuggable pipelines with strong SLAs around freshness, completeness, and latency
Implement backend services and APIs for telemetry ingestion, configuration management, metadata, and orchestration
Apply strong software engineering practices including object-oriented design, automated testing, CI/CD, and code reviews
Establish automated data quality checks, anomaly detection, alerting, lineage, and auditability across the platform
Provide technical leadership by setting platform direction, reviewing designs, mentoring engineers, and influencing product and engineering roadmaps

What we offer

Robust health coverage. Excellent health, dental and vision insurance covered up to 100% by ALSO with FSA & HSA options
One Medical membership and dedicated insurance advocates
Rich fertility and family building benefits with Progyny
Flexible time off
401(k) match

Fulltime

Senior .NET Software Engineer (Data Infrastructure)

At the core of Bentley's global infrastructure solutions lies a critical data se...

Location

Lithuania , Vilnius; Kaunas

Salary:

4000.00 EUR / Month

Bentley Systems

Expiration Date

Until further notice

Requirements

A Bachelor’s degree in Computer Science, Software Engineering, or a related field
At least 5 years of proven experience in software development with C#, .NET Core, and a strong understanding of OOP, data structures, and test frameworks
Expert-level, hands-on experience with major object storage platforms (Azure Blob Storage, Google Cloud Storage, AWS S3). This must include deep knowledge of storage usage optimization, lifecycle policies, and designing cost-efficient data access patterns
Solid experience with Docker and Kubernetes for deploying and managing containerized applications
Proven ability to write clean, maintainable, testable, and secure code, with an intuitive understanding of the long-term impact of architectural decisions
A self-motivated and proactive mindset, with the ability to work effectively as an individual contributor and as part of a high-performing team in an Agile/Scrum environment
Strong verbal and written communication skills in English

Job Responsibility

Architecting for Scale & Stability: Design and develop robust, event-driven cloud services and core components, with a primary focus on stability, performance, and long-term maintainability
Modernizing Our Storage Solutions: Implement and optimize solutions using the latest cloud object storage technologies (Google Cloud storage, Azure Blob, AWS S3, etc.) to enhance performance and cost-efficiency
Hands-On Implementation: Use the latest .NET development tools to turn complex architectural designs into high-quality, production-ready software
Championing DevOps & Automation: Develop and utilize fully automated CI/CD pipelines to deliver both application and infrastructure changes seamlessly and safely into production
Driving Technical Excellence: Mentor and share your deep expertise with colleagues, elevating the team's technical capabilities
Ensuring System Health: Support the existing code base, troubleshoot complex production issues, and collaborate across teams to ensure end-to-end service reliability

What we offer

A great Team and culture
An exciting career as an integral part of a world-leading software company
An attractive salary and benefits package
A commitment to inclusion, belonging and colleague wellbeing
Training and professional development opportunities (certifications programs, conferences etc.)
Additional annual leave days and extra paid days for different occasions (marriage, moving day, bereavement leave etc.)
Health insurance package and accidents insurance 24/7
Referral program with bonuses
Extra paid day for volunteering in the organization of your choice
Ability to work from office or hybrid from home

Fulltime

Staff Observability Data Infrastructure Engineer

CVS Health is seeking a highly skilled Observability Data Infrastructure Enginee...

Location

United States , Work at Home, Maryland

Salary:

130295.00 - 260590.00 USD / Year

CVS Health

Expiration Date

June 30, 2026

Requirements

7+ years of experience building and operating log, metric, and trace pipelines in Data, Security Data, or Observability Engineering roles
5+ years of hands-on experience with Databricks, Apache Spark, or other large-scale distributed data platforms
5+ years of experience working across cloud platforms (AWS, Azure, or GCP), including storage, compute, and event-driven services
5+ years of production experience using SQL and Python in data-intensive environments
3+ years of experience with enterprise observability platforms (Splunk, Datadog, Elastic, or equivalent)
3+ years of experience with high-throughput ingestion and streaming technologies such as Cribl, Vector, or Kafka
3+ years of experience designing telemetry systems aligned to OpenTelemetry (OTEL) or similar standards
Bachelor's degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience)

Job Responsibility

Design, build, and operate high-volume log, metric, and trace pipelines using Databricks, cloud data lakes, and distributed processing engines
Architect and evolve an Observability Lakehouse aligned with OpenTelemetry (OTEL) data models and standards
Implement ingestion and transformation workflows using technologies such as Cribl, Vector, Jenkins, GitHub Actions, or equivalent tools
Normalize, model, and enrich telemetry data to support detection engineering, forensics, and operational analytics
Develop scalable ETL/ELT frameworks, Delta Lake architectures, and automated data quality validation for unstructured and semi-structured data
Partner with Security Engineering, SRE, Cloud, and SOC teams to improve enterprise visibility and detection accuracy
Build and maintain CI/CD pipelines and reusable Infrastructure-as-Code (IaC) patterns for observability platform deployment
Identify and resolve performance, latency, cost, and reliability issues across telemetry pipelines
Contribute to engineering standards, documentation, and knowledge sharing across observability and security platforms

What we offer

Medical, dental, and vision coverage
Paid time off
Retirement savings options
Wellness programs
Bonus, commission or short-term incentive program
Equity award program

Fulltime

Performance Infrastructure Engineer- Data Center GPU

You will be part of a small, but dedicated team driving discrete GPU products’ p...

Location

United States , Santa Clara

Salary:

192000.00 - 288000.00 USD / Year

AMD

Expiration Date

Until further notice

Requirements

Strong development experience in Python and/or Bash (or equivalent scripting languages)
Experience with Github, Jenkins, or similar CI/CD and code review systems
Linux system administration experience preferred
Experience developing automated test infrastructure and orchestrating multisystem workflows is preferred
Ansible experience is a bonus
Strong analytical, problem solving, and debugging skills
Excellent communication skills
must be a critical thinker and self-starter
Ability to quickly learn and apply new tools, technologies, and frameworks
Networking experience preferred, including common protocols and basic debugging

Job Responsibility

Technical team lead for a team of 5-6 engineers
Assess and understand the current automation and performance analysis infrastructure, identifying strengths, gaps, and opportunities for improvement
Collaborate with internal teams to gather technical requirements and understand evolving needs
Develop a forward looking plan that balances reusing existing systems with building new infrastructure where appropriate
Design, develop, and maintain automation and performance analysis tooling using Python, Bash, Make, and related technologies
Build and enhance workflow automation solutions using internally developed tools to orchestrate ML workloads
Develop new techniques and tooling to optimize ML workload execution, profiling, and analysis at scale

Staff Software Engineer, Data Infrastructure

At Docker, we make app development easier so developers can focus on what matter...

Location

United States , Seattle

Salary:

195400.00 - 275550.00 USD / Year

Docker

Expiration Date

Until further notice

Requirements

8+ years of software engineering experience with 3+ years focused on data engineering and analytics systems
Expert-level experience with Snowflake including advanced SQL, performance optimization, and cost management
Deep proficiency in DBT for data modeling, transformation, and testing with experience in large-scale implementations
Strong expertise with Apache Airflow for complex workflow orchestration and pipeline management
Hands-on experience with Sigma or similar modern BI platforms for self-service analytics
Extensive AWS experience including data services (S3, Redshift, EMR, Glue, Lambda, Kinesis) and infrastructure management
Proficiency in Python, SQL, and other programming languages commonly used in data engineering
Experience with infrastructure-as-code, CI/CD practices, and modern DevOps tools
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Proven track record designing and implementing large-scale distributed data systems

Job Responsibility

Define and drive the technical strategy for Docker's data platform architecture, establishing long-term vision for scalable data systems
Lead design and implementation of highly scalable data infrastructure leveraging Snowflake, AWS, Airflow, DBT, and Sigma
Architect end-to-end data pipelines supporting real-time and batch analytics across Docker's product ecosystem
Drive technical decision-making around data platform technologies, architectural patterns, and engineering best practices
Establish technical standards for data quality, testing, monitoring, and operational excellence
Design and build robust, scalable data systems that process petabytes of data and support millions of user interactions
Implement complex data transformations and modeling using DBT for analytics and business intelligence use cases
Develop and maintain sophisticated data orchestration workflows using Apache Airflow
Optimize Snowflake performance and cost efficiency while ensuring reliability and scalability
Build data APIs and services that enable self-service analytics and integration with downstream systems

What we offer

Freedom & flexibility
fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup
we want you comfortable while you work
16 weeks of paid Parental leave
Technology stipend equivalent to $100 net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity

Fulltime

Principal Data Infrastructure Engineer

As Microsoft continues to push the boundaries of AI, we are on the lookout for p...

Location

United States , Redmond

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering
OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering
OR equivalent experience
4+ years in Big Data Infrastructure, DevOps, SRE, or Platform Engineering
3+ years of hands-on experience managing and scaling distributed systems—from bare-metal to cloud-native environments
2+ years deploying containerized applications using Kubernetes and Helm/Kustomize
Solid scripting and automation skills using Python, Bash, or PowerShell
Proven success in CI/CD pipeline management, release automation, and production troubleshooting
Experience working with Databricks for scalable data processing and analytics
Familiarity with security practices in infrastructure environments, including IAM, OAuth, and Kerberos administration

Job Responsibility

Architect and maintain scalable, reliable, and observable Big Data Infrastructure for mission-critical AI applications
Champion DevOps and SRE best practices—automated deployments, service monitoring, and incident response
Build a self-service big data platform that empowers data and platform engineers and researchers
Develop robust CI/CD pipelines and automate infrastructure provisioning using Infrastructure as Code tools (Bicep, Terraform, ARM)
Collaborate with Data Engineers, Data Scientists, AI Researchers, and Developers to deliver secure, seamless big data workflows
Lead technical design reviews and uphold a clean, secure, and well-documented codebase
Proactively identify and resolve bottlenecks in data pipelines and infrastructure
Optimize system performance across storage, compute, and analytics layers
Partner with Security teams to enhance system security (IAM, OAuth, Kerberos)
Embody and promote Microsoft’s values: Respect, Integrity, Accountability, and Inclusion

Fulltime

Research Engineer, Data Infrastructure

As a Research Engineer in Data Infrastructure, you will design and implement a “...

Location

United States , Palo Alto

Salary:

180000.00 - 250000.00 USD / Year

1X Technologies

Expiration Date

Until further notice

Requirements

Strong experience in building data pipelines and ETL systems
Ability to design and implement systems that collect, upload, and manage data from robotic fleets
Familiarity with architectures combining on‑robot components, on‑premises clusters, and cloud systems
Experience with data labeling tools or building tooling for dataset visualization and annotation
Skills in creating or applying machine learning models for dataset organization / automated labeling

Job Responsibility

Optimize operational efficiency of data collection on the NEO fleet
Design triggers on the robot to determine if and when data should be uploaded
Automate ETL pipelines so fleet‑wide data is easily queryable and available for training
Work with external dataset providers to prepare diverse multi-modal pre-training datasets
Build frontend tools for visualizing and automating labeling of very large datasets
Develop machine learning models to automatically label and organize datasets

What we offer

Health, dental, and vision insurance
401(k) with company match
Paid time off and holidays

Fulltime

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Infrastructure Engineer (Data & Automations)

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