
Chief Architect
2 weeks ago
As a key member of our team, we are seeking an experienced Data Engineer to lead the design, development, and deployment of scalable data pipelines using Scala and Apache Spark.
The ideal candidate will have a strong background in functional programming concepts and extensive experience with Apache Spark and optimization techniques. They should also be proficient in Python and PySpark, with experience working with Databricks or similar cloud-based Spark platforms.
Key Responsibilities:
- Lead the design, development, and deployment of scalable data pipelines using Scala and Apache Spark.
- Develop and maintain data processing workflows in PySpark and Python.
- Collaborate with stakeholders to deliver robust data solutions.
- Architect and implement data ingestion, transformation, and integration solutions for structured and unstructured data.
- Optimize Spark jobs for performance and cost efficiency on cloud platforms.
- Lead a team of data engineers and enforce best practices in coding, testing, and deployment.
- Troubleshoot complex data pipeline issues.
Required Skills and Qualifications:
- Bachelor's or Master's degree in Computer Science or related field.
- 10+ years of professional experience in data engineering.
- Strong hands-on programming experience in Scala and functional programming concepts.
- Extensive experience with Apache Spark and optimization techniques.
- Proficiency in Python and PySpark.
- Experience working with Databricks or similar cloud-based Spark platforms.
- Solid understanding of distributed computing, big data architectures, and data modeling.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Familiarity with data storage technologies like HDFS, S3, Delta Lake, and relational/non-relational databases.
- Strong leadership skills and problem-solving abilities.
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