
Building Scalable Data Pipelines
2 days ago
We are looking for a skilled Data Engineer to join our team. The ideal candidate will have expertise in designing and implementing data pipeline architectures, creating and maintaining events/streaming based architecture/design, and identifying, designing, and implementing internal process improvements.
The Data Engineer will be responsible for building the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and 'big data' technologies. They will also create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
In addition, the Data Engineer will work with data scientists to strive for greater functionality in our data systems.
Required Skills and Qualifications- Proficiency in either Scala or Python: The candidate should be proficient in one of these programming languages and have hands-on experience in writing data pipelines and transformations.
- Expertise in Apache Spark: Strong hands-on expertise in Apache Spark is mandatory, including knowledge of how to write Spark jobs and tune/optimize them for better performance.
- Able to handle large datasets efficiently: The candidate should be able to handle large datasets efficiently and optimize Spark jobs (partitions, shuffles, caching, memory usage, etc.)
- Hands-on experience with dbt (Data Build Tool): Must have hands-on experience with dbt for data transformations and data modeling.
- Experience with big data tools: Experience with big data tools like HDFS/S3, Spark/Flink,Hive,Hbase, Kafka/Kinesis, etc., relational SQL and NoSQL databases, and data pipeline and workflow management tools is highly desirable.
- Experience with AWS/GCP cloud services: Familiarity with AWS/GCP cloud services is highly desirable.
- Experience supporting and working with cross-functional teams: The candidate should have experience supporting and working with cross-functional teams in a dynamic environment.
- Familiarity with object-oriented/object function scripting languages is highly desirable.
- Familiarity with stream-processing systems like Spark-Streaming/Flink, etc.
The ideal candidate will have 2+ years of experience in a Data Engineer role and have contributed to an open-source project. A strong analytic skills related to working with structured/unstructured datasets is highly desirable. Also, the candidate should have a few weekend side projects up on GitHub and a working knowledge of a backend programming language.
Key Responsibilities:
- Design and implement data pipeline architectures.
- Create and maintain events/streaming based architecture/design.
- Identify, design, and implement internal process improvements.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and 'big data' technologies.
- Create data tools for analytics and data scientist team members.
- Work with data scientists to strive for greater functionality in our data systems.
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