Senior Data Engineer
2 weeks ago
Roles and Responsibilities :
- Design, develop, and maintain a secure, available, and high-performing data platform.
- Build scalable and adaptable data pipelines to process data efficiently.
- Integrate and maintain various data sources, including databases, APIs, SaaS platforms, files, logs, and events.
- Engineer ETL pipelines, understanding delta loading and CDC in Snowflake.
- Create standardized datasets to meet diverse use case requirements.
- Collaborate with product and engineering teams to ensure seamless product integration with the data platform.
- Ensure data quality by automating quality control measures and resolving data issues before they arise.-
Act as a subject-matter expert on tables, systems, and processes.
Qualifications :
- 5+ years of experience as a Data Engineer, with strong experience in streaming technologies (Kafka, AWS MSK, AWS Kinesis, AWS Data Firehose, Snowpipe).
- Proficiency in cloud infrastructure and CloudOps, using IaC tools like Terraform and Pulumi.
- Hands-on experience with data warehouse technologies (i.e., Snowflake, AWS Redshift) and AWS data pipelines (Lambda, Glue, Step Functions).
- Expertise in Star/Snowflake schema design, data modeling, and MLOps.
- Fintech/Financial services industry experience is a plus.
- Proficiency in SQL and programming languages such as Python or Java.
- Experience with data analysis tools like Looker or Tableau, and libraries like Pandas, Numpy, Scikit-learn, and Jupyter notebooks.
- Familiarity with Git, GitHub, and JIRA.
Skills Required :
- Cloud/PaaS Technologies: Kafka, AWS MSK, Kinesis, Snowpipe, AWS Lambda.
- Infrastructure as Code (IaC): Terraform, Pulumi.
- Data Modeling & Pipelines: Snowflake schema, ETL, CDC, AWS Glue.
- Programming & Scripting: Proficiency in Python, Java, and working knowledge of SQL.
- Data Analysis & Visualization: Experience with Looker, Tableau, Pandas, Numpy.
- Version Control & Collaboration: Familiar with Git, GitHub, and JIRA.
Nice to Have :
- Experience migrating applications in highly regulated industries like Fintech.
- Focus on simplifying, automating, and building reusable components
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