Senior Data Engineer Job at Robert Half (Madison)

Senior Data Engineer

You will join the OneMIS stream, responsible for management, regulatory & risk r...

Location

Romania , Bucuresti

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

University degree in computer science or a comparable qualification
At least 5 years of experience as a Data Engineer, building scalable data pipelines and working with cloud-based data ecosystems
Strong expertise in SQL and hands‑on experience building performant datasets in BigQuery (or similar cloud data warehouses)
Proven experience with Python and PySpark for scalable data processing in distributed environments
Solid understanding of data modeling, ELT/ETL patterns, and data quality best practices
Experience with Google Cloud Platform, particularly BigQuery, Dataflow, Cloud Composer, GCS, or equivalent cloud data services
Hands‑on experience building scalable data pipelines (batch and near real‑time) in a cloud‑native environment
Proficiency with version control, CI/CD pipelines, and automated testing frameworks
Ability to troubleshoot and optimize performance across compute, storage, and processing layers

Job Responsibility

Build scalable data pipelines: Design and deliver batch and real-time ETL/ELT pipelines across cloud environments to support analytics and reporting
Develop SQL and BigQuery solutions: Write and optimize advanced SQL transformations and build performant, cost‑efficient BigQuery data models
Develop Python workflows: Implement scalable data processing solutions using Python and PySpark, ensuring maintainable and high‑quality code
Design data models and ensure quality: Build robust data models and apply validation practices to maintain accuracy and reliability
Build cloud‑native data solutions: Use GCP services such as BigQuery, Dataflow, Cloud Composer, Pub/Sub, and GCS to build and operate modern data platforms
Optimize performance and reliability: Troubleshoot complex pipeline issues and continuously improve compute, storage, and processing performance
Collaborate using strong engineering practices: Work with engineering, analytics, and business teams while contributing to CI/CD, code reviews, and testing standards

What we offer

Smooth integration and a supportive mentor
Pick your working style: choose from Remote, Hybrid or Office work opportunities
Our projects have different working hours to suit your needs
Sponsored certifications, trainings and top e-learning platforms
Private Health Insurance – it’s custom-made for you
Individual coaching sessions or accredited Coaching School
Epic parties or themed events for our people and their families

Fulltime

Senior Data Engineer

We are looking for a Senior Data Engineer to design, build, and maintain scalabl...

Location

Indonesia , Jakarta

Salary:

Not provided

Axa

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Statistics, Mathematics, or related fields
Minimum 3 years of experience in Data Engineering or Analytics
Strong skills in Python and SQL
Experience with databases and big data tools (e.g. Spark, Hadoop)
Familiar with cloud platforms (AWS, GCP, or Azure)
Good communication skills and ability to mentor junior engineers

Job Responsibility

Design, build, and maintain data pipelines and centralized data platforms
Integrate and transform data from multiple internal and external sources
Ensure data quality through validation, monitoring, and best practices
Provide clean, ready-to-use data for analytics and modeling needs
Automate data processing and delivery processes
Collaborate with cross-functional teams to align data solutions with business goals
Support data governance, security, and compliance requirements
Mentor junior data engineers and lead technical initiatives

Fulltime

Senior Data Engineer

As a Senior Data Engineer at Mozilla, you will be a key member of our Data Engin...

Location

Canada; United States

Salary:

Not provided

Mozilla

Expiration Date

Until further notice

Requirements

At a minimum, 4 years of professional experience in data engineering
Proficiency in SQL and Python, and an eagerness to integrate AI into data engineering workflows to help us scale
Experience mapping complex business processes into extensible, analytical data models
Strong software engineering fundamentals
Self directed execution
Collaborative spirit
A track record of recommending and implementing new data collection methods to improve data model quality
You have used data to answer specific questions and guide company decisions
You have experience with cloud distributed systems (we use GCP) including distributed databases, message queues or batch / stream processing
You ensure data is safe to depend on through smart orchestration, error handling, and idempotency

Job Responsibility

Build the pipes: Build and manage business data pipelines as well as transform Firefox telemetry data into structured high quality datasets
Make data make sense: Partner with data scientists, product, and marketing teams to turn complex datasets into the models and metrics that drive Mozilla's decisions
Be a guardian of data quality: Ensure datasets stay accurate and performant by using observability tools to monitor quality and joining a weekly triage rotation to resolve data issues
Evolve our platform: Partner with other data engineers and platform engineers to improve how we work
Maintain data integrity: Ensure data governance and privacy policies are implemented and enforced across the tens of terabytes of data flowing through systems daily

What we offer

Generous performance-based bonus plans
Rich medical, dental, and vision coverage
Generous retirement contributions with 100% immediate vesting
Quarterly all-company wellness days
Country specific holidays plus a day off for your birthday
One-time home office stipend
Annual professional development budget
Quarterly well-being stipend
Considerable paid parental leave
Employee referral bonus program

Fulltime

Senior Data Engineer

This role is categorized as hybrid. This means the successful candidate is expec...

Location

United States , Austin; Warren

Salary:

153000.00 - 227000.00 USD / Year

General Motors

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent experience
7+ years of data engineering/development experience, including Python or Scala, SQL, and relational/non-relational data storage. (ETL frameworks, big data processing, NoSQL)
3+ years of experience in distributed data processing (Spark) and container orchestration (Kubernetes)
Proficiency in data streaming in Kubernetes and Kafka
Experience with cloud platforms – Azure preferred
AWS or GCP also considered
Solid understanding of CI/CD principles and tools
Familiarity with big data technologies such as Hadoop, Hive, HBase, Object Storage (ADLS/S3), Event Queues
Strong understanding of performance optimization techniques such as partitioning, clustering, and caching
Proficiency with SQL, key-value datastores, and document stores

Job Responsibility

Assemble large, complex data sets that meet functional and non-functional business requirements
Identify, design, and implement process improvements, including automation, data delivery optimization, and infrastructure redesign for scalability
Lead and deliver data-driven solutions across multiple languages, tools, and technologies
Contribute to architecture discussions, solution design, and strategic technology adoption
Build and optimize highly scalable data pipelines incorporating complex transformations and efficient code
Design and develop new source system integrations from varied formats (files, database extracts, APIs)
Design and implement solutions for delivering data that meets SLA requirements
Work with operations teams to resolve production issues related to the platform
Apply best practices such as Agile methodologies, design thinking, and continuous deployment
Develop tooling and automation to make deployments and production monitoring more repeatable

What we offer

Health and wellbeing benefit programs
Medical
Dental
Vision
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation & holidays

Fulltime

Senior Data Engineer

We are seeking an experienced Senior Data Engineer to design, build, and optimiz...

Location

Sri Lanka

Salary:

Not provided

Creative Software

Expiration Date

Until further notice

Requirements

3-5 years of experience in Data Engineering or related fields
Strong expertise in SQL and at least one programming language (Python, Scala, or Java)
Hands-on experience with Azure data services such as Data Factory, Synapse, Databricks, Azure SQL, and Storage
Experience with on-premise data platforms, especially SQL Server and SSIS
Strong Power BI skills, including: Designing efficient data models (star schema, proper relationships), Writing optimized DAX measures, Applying best practices for performance, data loading, and semantic modeling, Supporting BI teams with dataset design and dashboard optimization
Solid experience building and maintaining ETL/ELT pipelines
Good understanding of data warehousing concepts, data governance, and data quality frameworks
Experience with version control and structured development workflows (Git, CI/CD)
Strong communication and ability to work with both technical and business teams
Excellent analytical and problem-solving abilities

Job Responsibility

Build and Manage Data Pipelines
Design Data Models & Warehouses
Optimize Existing Data Solutions
Work Across Cloud and On-Prem Platforms
Support BI & Visualization Teams
Lead and Collaborate
Leverage Multi-Platform Experience

Fulltime

Senior Data Engineer

This role is categorized as hybrid. This means the successful candidate is expec...

Location

United States , Austin, Texas; Warren, Michigan

Salary:

138700.00 - 175450.00 USD / Year

General Motors

Expiration Date

Until further notice

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or related field, or equivalent experience
5+ years of relevant full-time experience
or equivalent knowledge
Strong experience in data engineering, including pipeline development, data modeling, data integration, and production support for enterprise data platforms
Data engineering experience, including Python or Scala, SQL, and relational/non-relational data storage (ETL frameworks, big data processing, NoSQL)
Experience with cloud platforms – Azure preferred
AWS or GCP also considered
Proficiency with SQL, key-value datastores, and document stores
Design, build, and optimize scalable batch and streaming data pipelines using Databricks (Apache Spark, Delta Lake) to support Medallion Architecture
Experience with modern cloud data platforms, distributed processing, and production-grade data pipelines

Job Responsibility

Design, build, and productionize reliable, scalable, and secure data pipelines and data products in Azure Databricks that support AI, analytics, and operational use cases
Lead the transformation of raw data from multiple source systems into trusted, well-structured datasets suitable for downstream analytics, model development, and AI enablement
Drive improvements in internal processes, delivery patterns, and technical solutions that support broader functional strategy and increase team efficiency
Solve complex and non-standard data engineering problems using advanced analytical and problem-solving techniques, with strong ownership and sound technical judgment
Partner closely with data scientists, analysts, software engineers, product stakeholders, and business teams to ensure data is accessible, trustworthy, and aligned to business outcomes
Support AI and data science use cases by enabling high-quality feature-ready data, experimentation workflows, and scalable patterns for model development and deployment
Contribute to technical direction within the team, influence key engineering decisions in their area, and act as a go-to resource for peers and less experienced engineers
Mentor team members through technical guidance, knowledge sharing, and strong engineering practices consistent with Level 7 expectations

What we offer

Relocation benefits
medical
dental
vision
Health Savings Account
Flexible Spending Accounts
retirement savings plan
sickness and accident benefits
life insurance
paid vacation & holidays

Fulltime

Senior Data Engineer

The Data, Analytics and Reporting Technology team is responsible for a cross-cut...

Location

United States , San Francisco; Charlotte

Salary:

100000.00 - 196000.00 USD / Year

Wells Fargo

Expiration Date

Until further notice

Requirements

4+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
4+ years of experience creating analytics or data science solutions in Public Cloud (GCP, AWS, Azure)
4+ years of hands on experience of Python and/or Go for building data pipelines, libraries, and automation tooling
4+ years with GCP or equivalent open source orchestration tools (Composer/Airflow/Dataflow/Beam) and CI/CD (Git, Liquibase, ) for data workloads
2+ years of hands-on experience building and implementing predictive AI models using machine learning algorithms (e.g., regression, classification, forecasting).

Job Responsibility

Develop scalable, secure data pipelines from on-premise systems of record to Google Cloud Platform services (BigQuery, BigTable, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer)
Leverage and extend capability roadmaps for reusable frameworks and tooling (ingestion, transformation, quality, orchestration) actively being developed by the larger organization
Enable self‑service data consumption and governance by standardizing patterns, templates, and sandbox capabilities rather than one‑off pipelines
Support use cases for training, validation and monitoring leveraging BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, and Cloud Storage
Create standardized feature transformation pipelines and a common feature store with strong lineage, dictionary and high availability for models
Ensure appropriate cost, performance, and reliability of GCP data workloads (partitioning, clustering, storage classes, autoscaling strategies)
Develop transformation libraries in Python/SQL/Beam (e.g., common SCD patterns, data quality checks, masking/tokenization routines)
Provide orchestration capabilities via Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration
Implement robust data modeling (dimensional, data vault, or canonical models) and semantic layer implementations with BigQuery or similar tools
Enforce data quality, lineage, and observability using standardized metrics, validation rules, and monitoring dashboards

What we offer

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement

Fulltime

Senior Data Engineer

We are looking for an experienced Senior Data Engineer to design, build, and opt...

Location

Bulgaria , Sofia

Salary:

Not provided

Valtech

Expiration Date

Until further notice

Requirements

Strong hands-on experience with Apache Spark and Delta Lake
Strong programming skills in Python and SQL
Proven experience building batch and streaming data pipelines and production-grade data platforms
Solid understanding of data modeling, data quality, and governance principles
Experience with one or more major cloud platforms, with preference for Microsoft Azure / Fabric, as well as AWS or GCP
Familiarity with modern data platforms such as Databricks and Snowflake
Experience with lakehouse architectures and distributed data systems
Strong understanding of scalability, reliability, and performance considerations in data pipelines
Strong problem-solving skills focused on scalability and reliability
Collaborative approach to working in cross-functional teams

Job Responsibility

Design and implement scalable data platforms and pipelines across cloud environments using technologies such as Spark and Delta Lake
Build ingestion, transformation, and curation workflows for both structured and unstructured data
Implement modern data architectures including lakehouse patterns and medallion layering
Deliver high-quality datasets that support analytics, machine learning, causal modeling, and optimization systems
Enable data pipelines for GenAI use cases including LLMs, RAG pipelines, and vector-based data flows
Design scalable logical and physical data models for analytical and operational use cases
Orchestrate workflows using tools such as Airflow, dbt, Lakeflow, or equivalents
Apply modern architecture patterns including event-driven and streaming architectures
Ensure adherence to best practices in data governance, lineage, quality, and access control
Establish strong data observability

What we offer

Flexibility with hybrid work options and 25 vacation days
Co-subsidized transportation & Multisport cards
Premium health insurance
Training policy for technical and other skills-related events, courses and certifications
Personal career development roadmap guided by performance evaluations
Self-care program offering psychological consultations & discussions
Cozy office space
Exciting team events and company gatherings

Fulltime

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