обновлено 7 часов назад
Data Engineer (Google Cloud)
125 000 - 140 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (Google Cloud): Building and optimizing enterprise data pipelines and a future-state Data Exchange platform with an accent on ETL, data quality, scalability, and operational intelligence. Focus on designing high-volume data workflows with BigQuery, Dataflow, Informatica, and Python, while leading delivery, securing sensitive data, and coordinating cross-functional engineering outcomes.
Location: Hybrid role based in Austin, TX or Southlake, TX, with regular in-person work expected.
Salary: USD $125,000–$140,000 per year, plus bonus or incentive opportunities.
Company
is a financial services company transforming its enterprise data platform to support investment services and business operations.
What you will do
- Provide technical and project leadership for data pipeline development and Agile delivery.
- Design, implement, and optimize end-to-end pipelines for large volumes of structured and unstructured data.
- Develop ETL processes integrating diverse sources into the enterprise data ecosystem.
- Implement data validation, quality checks, security controls, and access management.
- Collaborate with analysts, product owners, QA, project management, business teams, and technology operations to translate requirements into solutions.
- Mentor engineers, manage risks and dependencies, and maintain production support and deployment documentation.
Requirements
- At least 8 years of data engineering experience, including 2 years of project leadership in a matrixed organization.
- At least 3 years of experience in the financial services industry.
- Expertise in ETL development, data quality, exception handling, and data engineering best practices.
- Proficiency with SQL, Google Cloud products including BigQuery, Cloud Storage, Dataflow, Composer, and Pub/Sub, as well as SQL Server Integration Services.
- Expertise in Informatica IDMC/IICS and Python; experience using AI in the development lifecycle.
- Knowledge of data warehouses, data lifecycle management, metadata, governance, operational data exchanges, stakeholder management, and onshore/offshore delivery.
Nice to have
- Experience sourcing data from Workday, BMC Remedy Helix, Jira, Rally, or similar corporate systems.
- Experience guiding technical staff and managing multiple priorities in geographically dispersed environments.
- Experience with GitHub, Bamboo, Liquibase, and data pipeline patterns.
Culture & Benefits
- Hybrid work and flexibility with regular in-person collaboration.
- Health, dental, and vision insurance.
- 401(k) with company match and employee stock purchase plan.
- Paid vacation, volunteering time, parental leave, and family-building benefits.
- Tuition reimbursement and a 28-day sabbatical after five years for eligible positions.
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