Senior to Lead Data Engineer
F
FlodeskEmail Marketing
WorldwideFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonSQLAirflowdbtRedshift
Requirements
- 5+ years of experience in data engineering
- 1–2 years in a technical leadership or lead role
- Proven ability to design and scale data platforms for performance, reliability, and cost-efficiency
- Deep understanding of data architecture, modeling, and warehousing best practices
- Strong expertise in SQL
- Strong expertise in Python
- Experience with modern data pipeline tools (Airflow, Dagster, DBT)
- Familiarity with cloud platforms (AWS)
- Familiarity with cloud-native data services (S3, Redshift, Glue, Kinesis)
- Experience implementing streaming and real-time data processing solutions (strong plus)
- Passion for clean, maintainable code and strong documentation
- Excellent communication and stakeholder management skills
Responsibilities
- Define the data engineering vision and roadmap, aligned with business goals and analytics needs.
- Architect and lead the development of a scalable, high-performance data platform, including data lakehouse, data warehouses, and real-time pipelines.
- Mentor and guide a team of data engineers, fostering a culture of technical excellence, ownership, and continuous improvement.
- Establish and enforce best practices for data governance, quality, security, and compliance with regulations like GDPR and CCPA.
- Lead initiatives to implement state-of-the-art data engineering techniques, such as real-time streaming, data observability, and workflow orchestration.
- Collaborate cross-functionally with Product, Engineering, Analytics, and Infrastructure teams to ensure data systems meet evolving business and technical requirements.
- Continuously evaluate and introduce emerging tools and technologies to future-proof our data stack.
- Own the design and monitoring of ETL/ELT pipelines, ensuring reliability, cost efficiency, and high throughput.
- Champion data democratization, making high-quality, well-documented data available for downstream teams and use cases.
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