Sr. Data Engineer at EOS

Burlingame, California, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Mar, 26

Salary

160000.0

Posted On

18 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Modeling, ETL Development, Data Warehousing, SQL, Python, Cloud-Based Data Platforms, Data Governance, Data Security, Data Compliance, Real-Time Data Streaming, Machine Learning, Data Science Collaboration, Data Ecosystems, Data Services, Analytics

Industry

IT Services and IT Consulting

Description

OUR COMPANY: EOS IT Solutions is a Global Technology and Logistics company, providing Collaboration and Business IT Support services to some of the world’s largest industry leaders, delivering forward-thinking solutions based on multi-domain architecture. Customer satisfaction and commitment to superior quality of service are our top business priorities, along with investing in and supporting our partners and employees. We are a true International IT provider and are proud to deliver our services through global simplicity with trusted transparency. WHAT YOU WILL DO: As a Senior Data Engineer, you will lead data engineering initiatives and build end-to-end scalable, stable, and secure analytical solutions. You will work with massive datasets and be responsible for organizing and curating data for analytics. You will take a strategic and long-term view in architecting advanced data ecosystems, building efficient and scalable data services, and integrating data systems to support business intelligence and decision-making. KEY RESPONSIBILITIES: Design, implement, and operate large-scale, centralized high-volume, high-performance data structures for analytics and data science. Implement data ingestion routines, both real-time and batch, using best practices in data modeling and ETL/ELT processes. Collaborate with Project Managers to understand business and functional requirements and translate them into robust, scalable, and operable solutions with flexible data architecture. Assist software engineering teams in identifying key events and data to be logged for dashboarding and analytics. Continuously improve reporting and analysis processes, automating and simplifying self-service modeling and production support. ESSENTIAL CRITERIA: Degree in Computer Science, Engineering, Mathematics, or a related field, or 7+ years of industry experience. Strong experience in data modeling, ETL development, and data warehousing with technologies such as Oracle, Redshift, PostgreSQL, etc. Advanced SQL skills and expertise in query performance tuning. Proven ability to build data products incrementally and manage data sets from multiple sources. Proficiency in Python programming. DESIRABLE CRITERIA: Experience with cloud-based data platforms and services (e.g., AWS, Azure, GCP). Familiarity with data governance, security, and compliance best practices. Knowledge of real-time data streaming technologies (e.g., Kafka, Spark Streaming). Exposure to machine learning workflows and data science collaboration. The EOS pay range for this job is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, experience, education, knowledge, skills, and abilities, as well as internal equity, market data, or other laws. EOS is committed to creating a diverse and inclusive work environment and is proud to be an equal opportunity employer. We invite you to consider opportunities at EOS regardless of your gender; gender identity; gender reassignment; age; religious or similar philosophical belief; race; national origin; political opinion; sexual orientation; disability; marital or civil partnership status or other non-merit factor. Pay Range $140,000—$160,000 USD

Responsibilities

As a Senior Data Engineer, you will lead data engineering initiatives and build end-to-end scalable analytical solutions. You will work with massive datasets and be responsible for organizing and curating data for analytics.