G2 - Data Engineer II
Requirements
• We realize applying for jobs can feel daunting at times. Even if you don’t check all the boxes in the job description, we encourage you to apply anyway. • 4+ years of experience as a data engineer or ETL developer. • 2+ years of development experience with sound skills in data modeling, optimization, and database architecture. • Experience in the design and development of data pipelines using cloud and open-source tools. • Proficiency in writing and debugging SQL queries. • Good programming skills in Python or Java. • Must have good knowledge of performance tuning, optimization and debugging of data pipelines. • Working knowledge of the AWS data services (DynamoDB, RDS, Data Pipeline, EMR, Lambda, Glue, ECS, etc.) and cloud data warehouses like SnowFlake. • Proficiency in handling structured and unstructured data. • Proficiency in ELT/ELT tools like AWS Glue, Step Functions, Data Pipelines, Airflow, Airbyte, and DBT. • Familiarity with distributed computing and frameworks like Apache Spark, Hadoop, and Apache Kafka for handling large volumes of data. • Familiarity with software engineering principles and best practices. • What Can Help Your Application Stand Out: • Proficiency in data modeling, schema design, and optimizing data structures for performance in Snowflake. • Working experience in startup environments. • Experience with Agile process methodology, CI/CD automation, Test Driven Development. • Knowledge of data governance, security, and compliance standards within cloud-based data solutions. • Understanding of any reporting tools such as Tableau, Qlikview ,Looker, PowerBI, etc. • Database administration background. • Our Commitment to Inclusivity and Diversity • At G2, we are committed to creating an inclusive and diverse environment where people of every background can thrive and feel welcome. We consider applicants without regard to race, color, creed, religion, national origin, genetic information, gender identity or expression, sexual orientation, pregnancy, age, or marital, veteran, or physical or mental disability status. Learn more about our commitments here. • For job applicants in California, the United Kingdom, and the European Union, please review this applicant privacy notice before applying to this job. • How We Use AI Technology in Our Hiring ProcessG2 incorporates AI-powered technology to enhance our candidate evaluation process. These tools may assist with initial application screening, skills assessment analysis, and identifying candidates whose qualifications align with specific role requirements. While AI technology supports our recruitment workflow, all final hiring decisions remain under human oversight and judgment. • How We Use AI Technology in Our Hiring Process • Your Choice Matters: If you would prefer that your application be reviewed without AI assistance, you can opt out by entering your email address in the email entry field at the bottom of the Automated Processing Legal Notice. Choosing to opt out will not disadvantage your application in any way—we will ensure your materials receive a thorough manual review by our hiring team.For additional details about how we handle your information throughout the application process, please review G2's Applicant Privacy Notice. • Your Choice Matters:
Responsibilities
• Data infrastructure and processing: • Lead the design and development of data pipelines for seamless integration of data from various sources into the G2 Data Platform. • Optimize data pipelines, ensuring cost effectiveness, scalability, and reliability. • Constantly innovate to make the data stack follow the latest trends. • Service data requests from various users of the G2 data platform. • Actively contribute to data modeling and design reviews, striving for improved adoption and efficiency. • Execute the project tasks aligned with project timelines and objectives under the guidance of senior team members. • Develop repeatable and scalable code that processes data to ensure data availability in the platform is as real-time as possible. • Actively contribute to the development and advancement of the data platform. • Promote architectural changes that increase the scalability of our data infrastructure while maintaining efficiency in all phases of the development lifecycle. • Data quality assurance and governance : • Learn and adopt best practices in data engineering to contribute to robust solutions. • Own the implementation of data quality and data governance initiatives and drive them to completion. • Recommend and ensure the data platform follows privacy and security standards and requirements. • Document data architecture, data model, and workflows for how it should be consumed. • Mentorship and Collaboration : • Guide junior engineers by providing technical support, expertise, best practices, and constructive feedback on data engineering techniques. • Collaborate with peers, actively participating in knowledge sharing sessions and contributing to a collaborative team environment. • Seek guidance and mentorship from senior team members to enhance technical and analytical skills.
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