Offer summary

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related fields., At least 4 years of experience in data engineering, especially with SQL, BigQuery, and GCP., Strong expertise in Apache Iceberg, Starburst, and Trino for large-scale data processing., Proficiency in SQL, cloud data services, and experience with data pipeline development using Python, Java, or Scala..

Key responsibilities:

Design and implement scalable data architectures and ETL/ELT pipelines.

Collaborate with data scientists, analysts, and stakeholders to understand data needs.

Build and maintain data pipelines and storage solutions on Google Cloud Platform.

Monitor, troubleshoot, and optimize data workflows for performance and reliability.

Job description

We are seeking a skilled Data Engineer to design, build, and optimize data pipelines and analytics platforms. This role will focus on developing scalable, efficient, and highperformance data solutions that support advanced analytics, business intelligence, and machine learning applications. The ideal candidate is passionate about data engineering, cloudbased data architectures, and modern data processing frameworks.

Key Responsibilities:

Data Architecture & Engineering:
- Design and implement scalable data architectures leveraging BigQuery, Iceberg, Starburst, and Trino.
- Develop robust, highperformance ETLELT pipelines to process structured and unstructured data.
- Optimize SQL queries and data processing workflows for efficient analytics and reporting.
- - Cloud & Big Data Infrastructure:
    - Build and maintain data pipelines and storage solutions using Google Cloud Platform (GCP) and BigQuery.
    - Implement best practices for data governance, security, and compliance within cloudbased environments.
    - Optimize data ingestion, storage, and query performance for highvolume and highvelocity datasets.
    - - Data Processing & Analytics:
        Leverage Apache Iceberg for largescale data lake management and transactional processing.
        Utilize Starburst and Trino for distributed query processing and federated data access.
        Develop strategies for data partitioning, indexing, and caching to enhance performance.
        Collaboration & Integration:
        Work closely with data scientists, analysts, and business stakeholders to understand data needs and requirements.
        Collaborate with DevOps and platform engineering teams to implement CICD pipelines and infrastructureascode for data workflows.
        Integrate data from multiple sources, ensuring data integrity and accuracy across systems.
        Performance Optimization & Monitoring:
        Monitor, troubleshoot, and optimize data pipelines for efficiency, scalability, and reliability.
        Implement data quality frameworks and automated validation checks to ensure consistency.
        Utilize monitoring tools and performance metrics to proactively identify bottlenecks and optimize queries.
        Qualifications:Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
        Experience:
        4+ years of experience in data engineering, with expertise in SQL, BigQuery, and GCP.
        Strong experience with Apache Iceberg, Starburst, and Trino for largescale data processing.
        Proven track record of designing and optimizing ETLELT pipelines and cloudbased data workflows.
        Technical Skills:
        Proficiency in SQL, including query optimization and performance tuning.
        Experience working with BigQuery, Google Cloud Storage (GCS), and GCP data services.
        Knowledge of data lakehouse architectures, data warehousing, and distributed query engines.
        Handson experience with Apache Iceberg for managing largescale transactional datasets.
        Expertise in Starburst and Trino for federated queries and crossplatform data access.
        Familiarity with Python, Java, or Scala for data pipeline development.
        Experience with Terraform, Kubernetes, or Airflow for data pipeline automation and orchestration.
        Preferred Skills:Understanding of machine learning data pipelines and realtime data processing.
        Experience with data governance, security, and compliance best practices.
        Exposure to Kafka, PubSub, or other streaming data technologies.
        Familiarity with CICD pipelines for data workflows and infrastructureascode.
        At Inmar, we put people first and that means empowering our associates to thrive at every stage of life and career. Our comprehensive and competitive benefits package is thoughtfully designed to support a wide range of lifestyles and life stages.
        Eligible associates have access to:
        Medical, Dental, and Vision insurance
        Basic and Supplemental Life Insurance options
        401(k) retirement plans with company match
        Health Spending Accounts (HSAFSA)
        We also offer:
        Flexible time off and 11 paid holidays
        Familybuilding benefits, including Maternity, Adoption, and Parental Leave
        Tuition Reimbursement and certification support, reflecting our commitment to lifelong learning
        Wellness and Mental Health counseling services
        Concierge and worklife support resources
        Adoption Assistance Reimbursement
        Perks and discount programs
        Please note that eligibility for some benefits may depend on your job classification and length of employment. Benefits are subject to change and may be governed by specific plan or program terms.
        We are an Equal Opportunity Employer, including disabilityvets.
        This position is not eligible for student visa sponsorship, including F1 OPT or CPT. Candidates must have authorization to work in the U.S. without the need for employer sponsorship now or in the future.