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Sr. Cloud Data Engineer

Job Title: Sr. Cloud Data Engineer Location: Alpharetta, GA (Hybrid: Tue & Thu in Office) Duration: 12 Months' Overview: We are seeking a highly skilled Data Engineer / Cloud Data Solutions engineer with experience in Google Cloud Platform (GCP) to design, build, and optimize scalable data solutions. The ideal candidate will have a strong background in data engineering, data modeling, and data analysis, and will be proficient in cloud-based architectures. You will be responsible for architecting, developing, and maintaining data pipelines, optimizing data lifecycle processes, and creating insightful reports and dashboards that drive decision-making. In this role, you will work closely with cross-functional teams to design robust data models and analytics solutions, utilizing your skills in BigQuery, Python, PySpark, LookML, SQL, GCP Data Studio, and GCP Data Flow. Your ability to tell compelling data stories and translate complex data into actionable insights will be crucial to your success. Key Responsibilities: Design, develop, and manage scalable data architectures and pipelines on Google Cloud Platform (GCP). Build and optimize complex data models and ETL processes using BigQuery, LookML, Python, PySpark, and SQL. Utilize GCP Data Flow and other GCP services to automate data processing and orchestration. Leverage GCP Looker Studio to create insightful dashboards and reports that provide business value. -Collaborate with data scientists, analysts, and other stakeholders to gather requirements and translate them into technical solutions.Conduct data analysis to identify trends, patterns, and insights to support data-driven decision-making. Apply advanced data modeling techniques to ensure data quality, integrity, and consistency. Manage and optimize the entire data lifecycle, from ingestion to archiving and deletion. Develop and implement best practices for data governance, security, and compliance on GCP. Communicate complex data findings to non-technical stakeholders through storytelling and data visualization. Qualifications: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field. 8 years of hands-on experience in data engineering, data modeling, and analytics on Google Cloud Platform (GCP). Proficient in BigQuery, LookML, Python, PySpark, and SQL for data processing and analysis.

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What You Should Know About Sr. Cloud Data Engineer, eTeam

Are you a passionate and skilled Sr. Cloud Data Engineer looking for your next challenge in a vibrant tech environment? Join us in Somerset, NJ, where innovation meets collaboration, as we seek a Sr. Cloud Data Engineer! In this role, you'll have the opportunity to design, build, and optimize scalable data solutions using the Google Cloud Platform (GCP). With your extensive experience in data engineering, data modeling, and data analysis, you'll be a key player in architecting and maintaining robust data pipelines that drive informed decision-making across the organization. Collaborating with talented cross-functional teams, you'll harness your expertise with tools like BigQuery, Python, and PySpark to produce insightful reports and dashboards using GCP services. You’ll also be instrumental in optimizing data lifecycle processes and ensuring data quality, integrity, and security. If you're eager to translate complex data into compelling stories that empower stakeholders, this is the perfect opportunity for you. We value teamwork and encourage a creative, problem-solving mindset that will help us grow and thrive together. Come and be part of our dynamic team and contribute to meaningful projects that make a difference!

Frequently Asked Questions (FAQs) for Sr. Cloud Data Engineer Role at eTeam
What are the primary responsibilities of a Sr. Cloud Data Engineer at this company?

As a Sr. Cloud Data Engineer, your primary responsibilities will include designing and managing scalable data architectures on Google Cloud Platform (GCP), building and optimizing data models, and creating ETL processes using tools like BigQuery and Python. You'll also collaborate with teams to ensure data quality and create insightful analytics solutions.

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What qualifications are required for the Sr. Cloud Data Engineer role at this company?

To qualify for the Sr. Cloud Data Engineer position, candidates typically need a Bachelor's or Master's degree in Computer Science or a related field, along with at least 8 years of hands-on experience in data engineering on GCP. Proficiency in tools like BigQuery, PySpark, and SQL is essential.

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How does the Sr. Cloud Data Engineer contribute to data-driven decision-making?

The Sr. Cloud Data Engineer plays a critical role in data-driven decision-making by designing data pipelines that process and analyze large datasets, generating insightful reports and dashboards that enable stakeholders to make informed business decisions based on concrete data.

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What technologies should a Sr. Cloud Data Engineer be familiar with for this role?

Candidates for the Sr. Cloud Data Engineer position should be well-versed in Google Cloud Platform (GCP) technologies, particularly BigQuery, GCP Data Flow, LookML, Python, PySpark, and SQL. Experience with data visualization tools such as GCP Looker Studio is also highly beneficial.

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What opportunities for collaboration exist for a Sr. Cloud Data Engineer at this company?

As a Sr. Cloud Data Engineer, you will collaborate with various teams, including data analysts, data scientists, and business stakeholders, to gather requirements and create technical solutions that address complex data challenges while ensuring effective communication across departments.

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Common Interview Questions for Sr. Cloud Data Engineer
Can you explain your experience with Google Cloud Platform as a Sr. Cloud Data Engineer?

During the interview, be sure to highlight specific GCP projects you've worked on, detailing your role in designing data architectures and using services like BigQuery and Data Flow. Sharing results, such as improved processing times or enhanced dashboard insights, can make your answer compelling.

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What strategies do you use for optimizing ETL processes?

Discuss techniques like partitioning and indexing in BigQuery, as well as the use of GCP Data Flow for orchestration. Highlight results from previous roles, emphasizing any efficiency gains or reduction in load times achieved through your optimizations.

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How do you ensure data quality and integrity in your data pipelines?

Explain your approach to data validation, cleansing, and quality checks throughout the data pipeline. Discuss practical examples where you implemented data governance best practices to maintain data consistency and reliability.

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Describe a challenging data problem you've solved as a Sr. Cloud Data Engineer.

Share a specific challenge you faced, what resources or solutions you used to address it, and the outcome. Be sure to emphasize your problem-solving skills and the impact your solution had on the overall business process or data strategy.

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How do you collaborate with non-technical stakeholders?

Mention the techniques you use to translate complex data findings into understandable insights, such as storytelling with data visualizations. Provide examples of successful collaborations that led to actionable business strategies.

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What tools do you prefer for data visualization and reporting?

Discuss your familiarity with tools such as GCP Looker Studio and how you utilize them to create visualizations that enhance the interpretation of data. Share how your visualizations have driven key business decisions.

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How do you stay updated with the latest trends in data engineering?

Explain how you engage with industry blogs, attend webinars, or participate in forums and communities focused on GCP and data engineering trends. Mention any certifications or courses you've taken to further your knowledge.

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What is your experience with automated data processing?

Discuss specific automated workflows you've developed using GCP Data Flow or other tools. Highlight the efficiencies gained and how these solutions improved overall data lifecycle management.

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Can you share an example of how you used data analysis to support a business decision?

Provide a detailed example where your analysis revealed insights that influenced business strategy. Be specific about your methodology and the results of your findings.

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What aspects of data governance do you feel are most important in data engineering?

Talk about your understanding of data governance principles, including security, compliance, and data lifecycle management. Share experiences where you've implemented governance practices in your work that positively impacted data handling.

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Full-time, hybrid
DATE POSTED
December 21, 2024

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