3 дня назад
Mid-Level/Lead Data Engineer (Python, AWS, Spark)
85 500 - 130 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Mid-Level/Lead Data Engineer (Python, AWS, Spark): Building and scaling reliable analytical data products and pipelines for property and casualty insurance with an accent on automated ETL, distributed processing, cloud-native AWS services, and compliant data solutions. Focus on designing scalable data architectures, integrating structured and unstructured data, and solving complex data engineering challenges across enterprise platforms.
Location: Hybrid in Richardson, Texas; candidates must live within close proximity to the hub and work both from home and in the office. Applicants must be eligible to work lawfully in the U.S.; visa sponsorship is not available.
Salary: $85,500–$130,000 per year, plus potential yearly incentive pay of up to 15% of base salary.
Company
is an insurance company focused on helping customers, supporting communities, and delivering technology-enabled business solutions.
What you will do
- Build and scale reliable data products and pipelines supporting analytics, business decisions, growth, and customer retention.
- Develop reusable, scalable, secure, and compliant data solutions across platforms and compute environments.
- Acquire, cleanse, profile, transform, and load data for analytical discovery and production deployments.
- Design, deploy, support, and secure data technology in accordance with industry practices and regulations.
- Partner across teams to analyze technical needs, recommend solutions, and develop implementation and integration plans.
- Evaluate emerging data engineering technologies, tools, platforms, and data sources.
Requirements
- Professional experience as a Data Engineer.
- Programming experience with Python, Spark SQL or PySpark, R, Java, or Bash.
- Hands-on AWS experience with services including Glue, EMR Serverless, Lambda, Step Functions, EventBridge, S3, DynamoDB, Kinesis Firehose, Redshift, Iceberg, and SageMaker.
- Experience with Apache Spark or Databricks, infrastructure as code such as OpenTofu or Terraform, CI/CD, automated testing, security scans, and Airflow.
- Experience with relational databases, SQL, Athena, GitHub or GitLab, and automated data pipeline design and maintenance.
- Knowledge of data modeling and architecture, including star and snowflake schemas; ability to develop property and casualty data domain knowledge.
Culture & Benefits
- Collaborative Enterprise Technology environment focused on meaningful business impact.
- Health, dental, vision, telemedicine, mental health, and wellbeing programs.
- Training, tuition assistance, mentoring, and employee resource groups.
- Paid time off, holidays, parental leave, bereavement leave, and community service or education support days.
- Annual raises, bonuses, financial coaching, and a 401(k) plan with company contributions of up to 7%.
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