$111.40K - $133.80K/yr
Full-time
Posted 11 days ago
Job description
Technical/Functional Skills
1) Strong proficiency in SQL and database technologies
2) Familiarity with data warehousing and data modelling concepts
3) Hands-on experience with Google Cloud Platform (GCP) tools such as Big Query, Cloud Storage, Dataproc, Dataflow, Pub/Sub, and Bigtable
4) Experience with big data technologies such as Hadoop, Spark, Hive, Kafka etc
5) Familiarity with data warehousing and ETL tools such as Amazon Redshift, Google BigQuery, or Apache Airflow
6) Knowledge of Airflow and CI/CD pipelines
7) Exposure to data visualization tools such as Looker, PowerBI, Tableau etc
Roles & Responsibilities
• Design, develop, and maintain data architectures and infrastructure
• Collaborating with cross-functional teams to understand complex data requirements and deliver efficient solutions
• Design, build, and maintain data pipelines to support data ingestion, ETL, and storage
• Monitor, troubleshoot, and improve the performance and reliability of data systems.
• Monitor BigQuery usage and manage cost-effective scaling of resources.
• Develop and maintain data models to support analytics and reporting
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Frequently asked questions
Q: What skills or qualities help someone succeed as a Data Software Engineer?
A: To succeed as a Data Software Engineer, key technical skills include proficiency in programming languages such as Python, Java, or C++, as well as expertise in data structures, algorithms, and software development methodologies like Agile. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial, as Data Software Engineers often work with cross-functional teams and stakeholders to design, develop, and deploy data-driven solutions. By combining technical expertise with strong soft skills, Data Software Engineers can effectively drive business outcomes, innovate, and adapt to the rapidly evolving landscape of data technology.
Q: What is the career path for a Data Software Engineer?
A: A Data Software Engineer's typical career progression involves starting as a Junior Software Engineer, where they focus on developing and maintaining data-driven software applications, and gradually advancing to roles such as Senior Software Engineer, Technical Lead, or Data Architect, where they oversee large-scale data systems and lead cross-functional teams. Key opportunities for skill development include learning programming languages like Python, SQL, and Java, as well as data science tools like Hadoop, Spark, and machine learning frameworks like TensorFlow and PyTorch. Long-term, Data Software Engineers may pursue leadership roles, such as Director of Engineering or Chief Technology Officer, or transition into related fields like data science, product management, or entrepreneurship.
