GCP Data Engineer

As an experienced Data Engineer with expertise in Python, AWS, DBT, Airflow, Fivetran, and data streaming technologies, you will play a crucial role in building scalable, reliable, and secure data solutions. Key Responsibilities: - Develop and deploy data pipelines, both batch and streaming, into production with at least 5 years of experience. - Focus on ingesting, cleansing, and delivering high-quality data products using Google Cloud Platform (GCP). - Work with various relational SQL and NoSQL databases. - Utilize cloud-native data services, preferably Google Cloud Platform, including BigQuery, Vertex AI, Pub/Sub, Cloud Functions, etc. - Have deep expertise in one of the popular data warehousing tools such as Snowflake, BigQuery, RedShift, etc. - Utilize dbt (Data Build Tool) for data transformation. - Work with big data tools and frameworks like Hadoop, Spark, Kafka, etc., with familiarity in Databricks being a plus. - Proficient in object-oriented/object function scripting languages such as Python, Java, C++, Scala, etc. - Engage in the Data engineering Spectrum, developing metadata-based framework solutions for Ingestion, Processing, building Data Lake/Lake House solutions. - Possess strong knowledge of Apache Airflow for orchestration and workflow management. - Utilize Github/Git Toolkit for version control. - Provide operational support to stakeholders. - Expertise in standard software engineering methodology, including unit testing, test automation, continuous integration, code reviews, and design documentation. - Experience with CI/CD pipelines using Jenkins and Github Actions. - Familiarity with data visualization tools like Tableau, PowerBI, Looker, or similar tools is a plus. Qualifications Required: - Passionate and personable with a strong technical mindset. - Active in meetups, conferences, and webinars. - Aligned with Xebias values and culture. - Well-aware of Xebias business, Glassdoor ratings, and industry positioning. - Fit within the desired experience and salary range.,