Data Architect for Scalable Data Systems

6 days ago

Austin, Texas, United States Unreal Gigs Full time
Job Title: Data Architect for Scalable Data Systems

Estimated Salary: $150,000 - $200,000 per year

About Unreal Gigs

We are a leading provider of innovative solutions in the tech industry. Our team is passionate about staying ahead of the curve and delivering cutting-edge results.

Job Description

Data Engineering Role Overview

Unreal Gigs is seeking an experienced Data Architect to join our team and help us design, implement, and maintain scalable data systems. As a key member of our data engineering team, you will be responsible for architecting and implementing high-performance data pipelines using big data technologies such as Apache Spark, Kafka, and Hadoop.

In this role, you will collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to ensure seamless integration across systems. Your expertise in distributed systems, cloud infrastructure, and data storage management will be critical in ensuring that our data ecosystem is efficient, reliable, and scalable.

Key Responsibilities:

  1. Design and Build Scalable Data Pipelines:
  • Architect and implement data pipelines for ETL processes using tools like Apache Spark, Kafka, and Hadoop. You will create data workflows that handle high-volume, high-velocity data and ensure seamless integration across systems.
Optimize Big Data Storage and Processing:
  • Develop and manage data storage solutions (e.g., HDFS, S3, Cassandra) that are optimized for performance and cost-efficiency. You will configure distributed processing systems to support efficient data retrieval and transformation.
Collaborate on Data Strategy and Integration:
  • Work closely with data scientists, analysts, and other engineers to align big data architecture with analytics goals. You will ensure data availability and integrity across systems to support business objectives.
Implement Data Quality and Governance Standards:
  • Develop processes and tools to monitor data quality and enforce data governance policies. You will ensure data is accurate, reliable, and secure through regular checks and validation processes.
Enhance Data Processing with Automation:
  • Use tools like Apache Airflow or AWS Glue to automate data workflows and reduce manual processing. You will implement scripts and automation that streamline data handling and improve efficiency.
Monitor and Troubleshoot Data Systems:
  • Use monitoring tools to track system performance and address issues proactively. You will troubleshoot and resolve any bottlenecks or failures to maintain optimal data processing capabilities.
Stay Updated on Big Data Trends and Technologies:
  • Keep up with advancements in big data technologies and tools. You will integrate new techniques and platforms that align with business needs and promote innovation.

Requirements

Required Skills and Qualifications:

  • Big Data Platform Proficiency: Extensive experience with big data technologies such as Apache Spark, Hadoop, Kafka, and Hive. You are skilled at handling high-volume data and distributed processing.
  • Data Pipeline and ETL Knowledge: Proven ability to design, build, and maintain ETL processes for massive datasets. You can handle both real-time and batch data processing requirements.
  • Programming and Scripting: Proficiency in programming languages like Python, Java, or Scala for data processing and automation. Experience with SQL for data querying and manipulation is essential.
  • Cloud Data Services Expertise: Familiarity with cloud platforms such as AWS, GCP, or Azure, including their big data and storage services (e.g., S3, BigQuery, Azure Data Lake).
  • Data Quality and Governance: Strong understanding of data quality standards and governance practices, with experience in implementing data validation and monitoring frameworks.

Educational Requirements:

  • Bachelor's or Master's degree: In Computer Science, Data Engineering, Information Technology, or a related field. Equivalent experience in data engineering or big data management may be considered.
  • Certifications: In big data or cloud technologies (e.g., Cloudera Certified Data Engineer, AWS Certified Big Data – Specialty, Google Professional Data Engineer) are a plus.

Experience Requirements:

  • 5+ years of experience: In data engineering, with at least 3+ years focusing on big data technologies and high-scale data environments.
  • Experience in Distributed Systems: And large-scale data storage management.
  • Familiarity with Containerization: For deploying data processing environments is advantageous.

Benefits

  • Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
  • Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
  • Work-Life Balance: Flexible work schedules and telecommuting options.
  • Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
  • Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
  • Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
  • Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
  • Tuition Reimbursement: Financial assistance for continuing education and professional development.
  • Community Engagement: Opportunities to participate in community service and volunteer activities.
  • Recognition Programs: Employee recognition programs to celebrate achievements and milestones.

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