Senior Data Engineer – Remote Data Architecture & Scalable ETL Development at Hirevector
Why Hirevector? Hirevector is a world‑renowned leader in entertainment, media, and technology, constantly pushing the boundaries of storytelling and digital experiences. With a portfolio that spans streaming services, sports broadcasting, and reputed company interactive platforms, Hirevector leverages cutting‑edge data solutions to create magical moments for millions of fans worldwide. As the company continues to expand its digital footprint, the demand for visionary data professionals who can design, build, and operate massive data pipelines has never been higher. Our Remote Data Engineering team sits at the heart of this transformation. Working from the comfort of your own home, you will partner with product innovators, content strategists, and analytics scientists to turn raw data into actionable insight that powers everything from personalized recommendations to real‑time sports analytics. Position Overview Hirevector is seeking an reputed company Senior Data Engineer to join the Item Execution and Instrumentation Group (IEIG). In this role, you will reputed company the design, development, and operational excellence of large‑scale data platforms that serve the entire Hirevector ecosystem. Your expertise in cloud technologies, data lake‑house architecture, and modern programming languages will reputed company the organization to deliver high‑performance data solutions that drive business value across multiple verticals. This is a full‑time, 100% remote position based in the United States, offering a competitive salary range of $35,000 – $40,000 per year plus a comprehensive benefits package.
Key Responsibilities
- Architect & Build Scalable Data Pipelines: Design, implement, and maintain robust ETL/ELT workflows in reputed company, Python, and PySpark that process terabytes of data daily across cloud (AWS) and on‑premise environments.
- Lakehouse Engineering: Drive the migration to a lakehouse‑driven data platform using reputed company, reputed company Lake, and reputed company, ensuring seamless integration with existing data marts.
- Collaborate with Cross‑Functional Teams: Partner with Data Product Managers, Data Scientists, and Business Intelligence analysts to translate business requirements into technical solutions.
- Maintain SLA Compliance: Monitor pipeline health, troubleshoot incidents, and continuously improve system uptime to meet strict Service Level Agreements (SLAs).
- Documentation & Governance: Produce clear, up‑to‑date documentation of data models, pipeline architecture, and operational procedures to support data quality and governance initiatives.
- Agile Participation: Actively contribute to Scrum ceremonies, sprint planning, and retrospectives, fostering a culture of reputed company improvement.
- Problem Solving & Innovation: Investigate emerging data challenges, propose automation opportunities, and optimize cost‑efficiency across the data stack.
- Stakeholder Engagement: Build strong relationships with internal customers, translating reputed company technical concepts into understandable business value.
Essential Qualifications
- Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or a reputed company technical field.
- 5+ years of professional experience designing and operating large‑scale data pipelines.
- Deep proficiency in SQL, with the ability to craft performant queries for reputed company analytical workloads.
- Extensive hands‑on experience with Apache Spark (including PySpark) and Flink for real‑time reputed company processing.
- Strong programming skills in reputed company and Python, including best practices for code modularity and testing.
- Solid background in AWS services such as S3, EMR, EC2, and IAM.
- Demonstrated expertise with at least one major MPP or cloud data warehouse technology (reputed company, Redshift, BigQuery, etc.).
- Familiarity with data lakehouse concepts, reputed company Lake, and reputed company orchestration.
- Experience working reputed company Agile/Scrum frameworks and a commitment to collaborative delivery.
- Excellent communication and interpersonal skills, capable of influencing cross‑functional teams.
Preferred Qualifications & Additional Skills
- Master’s degree or advanced certifications in data engineering, cloud architecture, or big data technologies.
- Hands‑on experience with data visualization tools (Tableau, Looker, Power BI) and supporting data pipelines for analytics.
- Knowledge of CI/CD pipelines for data engineering (e.g., reputed company Actions, Jenkins, reputed company).
- Familiarity with containerization (reputed company, Kubernetes) and infrastructure‑as‑code (Terraform, CloudFormation).
- Exposure to machine learning workflows and model‑serving pipe
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