Senior Data Engineer

About Remote

Remote is solving global remote organizations’ biggest challenge: employing anyone anywhere compliantly. We make it possible for businesses big and small to employ a global team by handling global payroll, benefits, taxes, and compliance. Check out remote.com/how-it-works to learn more or if you’re interested in adding to the mission, scroll down to apply now.

Please take a look at remote.com/handbook to learn more about our culture and what it is like to work here. Not only do we encourage folks from all ethnic groups, genders, sexuality, age and abilities to apply, but we prioritize a sense of belonging. You can check out independent reviews by other candidates on Glassdoor or look up the results of our candidate surveys to see how others feel about working and interviewing here.

All of our positions are fully remote. You do not have to relocate to join us!

What this job can offer you

This is an exciting time to join the growing Data Team at Remote, which today consists of over 15 Data Engineers, Analytics Engineers and Data Analysts spread across 10+ countries. Throughout the team we're focused on driving business value through impactful decision making. We're in a transformative period where we're laying the foundations for scalable company growth across our data platform, which truly serves every part of the Remote business. This team would be a great fit for anyone who loves working collaboratively on challenging data problems, and making an impact with their work. We're using a variety of modern data tooling on the AWS platform, such as Snowflake and dbt, with SQL and python being extensively employed.

This is an exciting time to join Remote and make a personal difference in the global employment space as a Senior Data Engineer, joining our Data team, composed of Data Analysts and Data Engineers. We support the decision making and operational reporting needs by being able to translate data into actionable insights to non-data professionals at Remote. We’re mainly using SQL, Python, Meltano, Airflow, Redshift, Metabase and Retool.

What you bring

• Experience in data engineering; high-growth tech company experience is a plus
• Strong experience with building data extraction/transformation pipelines (e.g. Meltano, Airbyte) and orchestration platforms (e.g. Airflow)
• Strong experience in working with SQL, data warehouses (e.g. Redshift) and data transformation workflows (e.g. dbt)
• Solid experience using CI/CD (e.g. Gitlab, Github, Jenkins)
• Experience with data visualization tools (e.g. Metabase) is considered a plus
• A self-starter mentality and the ability to thrive in an unstructured and fast-paced environment
• You have strong collaboration skills and enjoy mentoring
• You are a kind, empathetic, and patient person
• Writes and speaks fluent English
• It's not required to have experience working remotely, but considered a plus

Key Responsibilities

• Playing a key role in Data Platform Development & Maintenance:
  • Managing and maintaining the organization's data platform, ensuring its stability, scalability, and performance.
  • Collaboration with cross-functional teams to understand their data requirements and optimize data storage and access, while protecting data integrity and privacy.
  • Development and testing architectures that enable data extraction and transformation to serve business needs.
• Improving further our Data Pipeline & Monitoring Systems:
  • Designing, developing, and deploying efficient Extract, Load, Transform (ELT) processes to acquire and integrate data from various sources into the data platform.
  • Identifying, evaluating, and implementing tools and technologies to improve ELT pipeline performance and reliability.
  • Ensuring data quality and consistency by implementing data validation and cleansing techniques.
  • Implementing monitoring solutions to track the health and performance of data pipelines and identify and resolve issues proactively.
  • Conducting regular performance tuning and optimization of data pipelines to meet SLAs and scalability requirements.
• Dig deep into DBT Modelling:
  • Designing, developing, and maintaining DBT (Data Build Tool) models for data transformation and analysis.