- Bachelor's degree in Computer Science, Engineering, Information Technology, or a
related quantitative field.
- 3+ years of professional experience in data engineering or a similar role, with a strong
focus on building and maintaining data pipelines.
- Proficiency in at least one programming language commonly used in data engineering
(e.g., Python, Java, Scala). Python is highly preferred.
- Strong experience with analytical engines like Apache Pinot and Elasticsearch..
- Hands-on experience with ETL/ELT tools and concepts.
- Proven experience with Google Cloud Platform (GCP) data services, specifically
BigQuery.
Competency in loading data into BigQuery using various methods (e.g., batch
loading from Cloud Storage, streaming inserts).
Strong SQL querying skills within BigQuery, including understanding of
BigQuery's unique SQL dialect and functions.
Familiarity with BigQuery table optimizations like partitioning and clustering.
Experience with BigQuery's data quality features or applying data quality best
practices to BigQuery data.
- Familiarity with data warehousing concepts and experience with data lake architectures.
- Understanding of data quality principles and experience implementing data validation
techniques.
- Experience with version control systems (e.g., Git).
- Excellent problem-solving skills and attention to detail.
- Strong communication and interpersonal skills, with the ability to explain complex
technical concepts to non-technical stakeholders.
