Senior Data Engineer
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- Worldwide
- Work type
- Remote
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Job Description
This is a remote position.
What You'll Do
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Design, implement, and manage complex DAGs and SubDAGs in Apache Airflow.
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Utilize Operators, macros, connections, variables, and XCom for efficient task execution.
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Conduct unit testing to ensure the robustness of Airflow workflows.
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Perform file operations and data movement between HDFS and S3 (and vice versa).
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Manage Hive external tables, update table DDL, and handle partition operations.
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Execute basic Hadoop commands and navigate/traverse HDFS.
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Work with Hive on Tez for optimized query execution.
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Utilize AWS command line tools for tasks such as listing and copying files from S3.
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Implement and manage secrets using tools like Ansible Vault and AWS Secrets Manager.
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Develop and optimize data processing tasks using PySpark.
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Understand and leverage Livy for efficient Spark job execution.
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Import and export data between Microsoft SQL Server and HDFS using Sqoop.
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Apply dimension modeling principles, define facts and dimensions, and manage surrogate keys.
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Implement effective branching strategies in Git.
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Participate in the process of raising and reviewing Merge Requests in GitLab.
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Utilize SSIS for migrating data workflows, ensuring a smooth transition.
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Model data in Snowflake, differentiating between external and internal tables.
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Understand the use of views and materialized views in Snowflake.
What You'll Need
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Bachelor's degree in Computer Science, Information Technology, or a related field.
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Proficient in Python (both Python 2.7 and 3.6+).
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Experience in unit testing and test-driven development.
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Familiarity with Secrets Management tools and techniques.
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Knowledge of data modeling principles and practices.
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Strong understanding of Git version control and GitLab workflows.
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Excellent problem-solving and communication skills.
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Awareness or knowledge of IT security best practices as defined by ISO / SOC or similar standards.
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Experience with SSIS for data migration workflows.
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Experience with Snowflake (external/internal tables, views, materialized views).
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Familiarity with Hive on Tez for optimized query execution.
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Experience with AWS command line tools and S3 operations.
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Knowledge of Livy for efficient Spark job execution.
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Be part of a remote-first organization where flexibility is embraced.
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Work and learn alongside talented engineers and technology leaders.
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Explore opportunities to learn and grow through technical and non-technical training programs.
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Gain global exposure by working on products with international teams and clients.
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Attend virtual and in-person international technology conferences to expand your knowledge and network.
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Nursery reimbursement benefit and Aspire Wellness Program.
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Exposure to working in an IT environment that adheres to rigorous security and compliance standards defined by ISO / SOC.