Data Infrastructure Architect
13 hours ago
We're seeking a skilled Data Infrastructure Architect to design, develop, and optimize our data systems. As a key member of our team, you'll be responsible for constructing efficient, scalable data pipelines, ensuring data is accessible and usable for analysts, data scientists, and business stakeholders.
Key Responsibilities:
- Design and Develop Data Pipelines:
- Build and maintain robust, scalable, and efficient data pipelines to ingest, process, and store data from a variety of sources.
- Data Warehouse Management:
- Architect and maintain data warehouses or data lakes using cloud platforms (e.g., AWS Redshift, Google BigQuery, or Snowflake) to organize and store large-scale datasets.
- Collaborate with Data Scientists and Analysts:
- Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver datasets that meet business needs.
- Data Quality and Governance:
- Implement data quality checks and monitoring systems to ensure the accuracy, completeness, and consistency of data across the pipeline.
- Performance Optimization:
- Optimize the performance of data systems, ensuring fast and reliable data access.
- Automation and Monitoring:
- Automate data workflows, pipeline deployments, and data quality checks to minimize manual intervention.
- Data Security and Compliance:
- Implement security protocols to protect sensitive data, ensuring compliance with relevant regulations such as GDPR, HIPAA, or SOC2.
Requirements:
Required Skills:
- Data Engineering Expertise: Strong experience building and maintaining data pipelines, ETL processes, and data warehouses using cloud platforms (AWS, GCP, Azure).
- Programming and Scripting: Proficiency in languages such as Python, SQL, or Scala, and experience with data engineering tools like Apache Spark, Airflow, or Kafka.
- Data Warehousing and Storage: Expertise in managing and optimizing data warehouses or data lakes (e.g., Redshift, BigQuery, Snowflake).
- Database and Query Optimization: Strong knowledge of database design and query optimization for performance.
- Data Governance and Security: Solid understanding of data governance practices, security protocols, and compliance regulations.
Educational Requirements:
- Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related field.
- Certifications in cloud platforms (AWS, GCP, Azure) or data engineering technologies (e.g., Apache Hadoop, Apache Spark) are a plus.
Experience Requirements:
- 3+ years of experience in data engineering, with hands-on experience building and managing data pipelines, data warehouses, and cloud-based storage solutions.
- Proven experience working with big data technologies and distributed systems, optimizing data flows and processes to handle large datasets.
- Familiarity with data quality, data governance, and data security best practices is highly desirable.
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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