Job Description
A data engineer responsible for developing and maintaining end-to-end data pipelines, managing data integration and transformation, and supporting analytics and automation initiatives within a cloud-based data platform to enable data-driven decision making across various business functions.
Key Responsibilities
- Develop and maintain end-to-end data pipelines and backend ingestion processes.
- Build and enhance the data platform to support automation and analytics.
- Integrate and transform data from various sources to ensure interoperability and data quality.
- Manage critical data pipelines to support growth initiatives and advanced analytics.
- Develop data products using SQL and Python for use by customer systems and internal teams.
Requirements
- A Bachelor’s degree in computer science, data engineering, data science, information technology, or equivalent engineering program.
- 5 years of work experience as a data engineer, including 3 years of experience in designing, developing, testing, and maintaining end-to-end data pipelines.
- Experience with modern cloud-based data-lake and data-warehousing technology stacks, and familiarity with typical data-engineering tools, ETL/ELT processes, and data-warehousing best practices.
- Experience with programming languages Python and SQL.
- Exposure to ETL tools such as Fivetran, DBT, or equivalent.
- Experience with Python-based API frameworks for data pipelines.
- Experience working with RDBMS such as MySQL, AWS RDS Aurora MySQL, PostgreSQL, Oracle, MS SQL-Server, or equivalent.
- Experience with cloud platforms including AWS, Azure, and/or GCP.
- Experience with data warehouse solutions such as Databricks, Google BigQuery, AWS Redshift, Snowflake, or equivalent.
- Ability to work with business customers to gather requirements and understand varied datasets.
- A self-starter, motivated, responsible, innovative, and technology-driven individual who performs well both solo and as a team member.
- Proactive problem solver with good communication skills and project management abilities to relay findings and solutions across technical and non-technical audiences.
- Experience with ETL and orchestration tools such as Fivetran, Alteryx, or equivalent.
- Experience with logging and monitoring tools such as Splunk, DataDog, AWS CloudWatch, or equivalent.
- Experience with AWS Serverless services including API Gateway, Lambda, S3, SNS, SQS, SecretsManager.
- Experience with containerization and orchestration tools such as Docker, Kubernetes, AWS ECR, AWS Fargate, and AWS IAM.
Benefits & Perks
Full time employees receive a competitive total compensation package
Employee-led remote and flexible working
Health benefits
Flexible working model including in-office, hybrid, and remote options
Ready to Apply?
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