Data Analytics Engineer

3 weeks ago

Agra, India Shop Suki Full time

Job Title: Analytics Engineer

Department: Data & Analytics

Reports To: Head of Data & Analytics

 

Job Summary:

We are seeking an accomplished Analytics Engineer with deep expertise in data engineering, data modeling, and enabling self-service analytics. This role will be instrumental in transforming raw data into structured, highly optimized datasets and creating scalable data marts to empower self-service analytics across the organization. Leveraging Google Cloud Platform (GCP) services such as Google Cloud Storage, BigQuery and Dataform, the ideal candidate will have a robust background in data pipeline development, advanced SQL, and cloud-based data warehousing. Additional experience with on-premise PostgreSQL systems and familiarity with the retail sector will be advantageous.

 

Key Responsibilities:

●     Data Pipeline Engineering: Design, develop, and maintain complex ETL/ELT pipelines using Dataform, ensuring data integrity and optimal performance across the analytics infrastructure.

●     Data Mart Creation: Architect, develop, and manage scalable, high-performance data marts within BigQuery to support various business units in their analytical needs.

●     Advanced Data Modeling: Design and implement robust data models that underpin data marts and enable efficient data retrieval for reporting and analytics.

●     Self-Service Analytics Enablement: Collaborate with business units to design and deploy self-service analytics frameworks, empowering end-users with the tools and data they need to generate insights independently.

●     Cloud Data Integration: Lead the integration of disparate data sources into a unified cloud-based data warehouse, optimizing data flow and storage within GCP, particularly leveraging Google Cloud Storage and BigQuery.

●     Performance Optimization: Continuously monitor, refine, and optimize SQL queries, data models, and data processing workflows to maximize efficiency and minimize latency.

●     Collaboration and Support: Partner closely with data analysts, solution architects, devops engineers, and business stakeholders to ensure that data solutions are aligned with organizational needs and drive strategic decision-making.

●     PostgreSQL Integration: Provide expertise in integrating on-premise PostgreSQL systems with cloud-based data infrastructure, ensuring seamless data synchronization and accessibility.

●     Technical Documentation: Create and maintain detailed documentation for data models, ETL/ELT processes, data marts, and self-service analytics frameworks, ensuring clarity and reproducibility.

●     Continuous Improvement: Stay at the forefront of data engineering technologies and methodologies, driving continuous improvement initiatives across the data pipeline and analytics environments.

 

Skills/Competencies:

●     Expertise in Data Engineering: Extensive experience in building and managing data pipelines, with a focus on ETL/ELT processes within cloud environments.

●     Advanced SQL and BigQuery: Proficiency in advanced SQL and deep experience with BigQuery, including data partitioning, clustering, and performance tuning.

●     Data Mart Development: Strong experience in designing, implementing, and managing data marts that support diverse analytical requirements.

●     Self-Service Analytics: Proven ability to develop and implement self-service analytics solutions that enable end-users to generate insights independently.

●     Dataform Mastery: In-depth knowledge of Dataform or similar data transformation tools, enabling efficient data wrangling and transformation at scale.

●     PostgreSQL Proficiency: Strong understanding of PostgreSQL, including database design, indexing, and query optimization.

●     Analytical and Problem-Solving Skills: Exceptional ability to troubleshoot and resolve complex data-related issues, optimizing data structures and processes for peak performance.

●     Cross-Functional Collaboration: Strong communication skills, with a proven track record of working effectively across technical and business teams to deliver impactful data solutions.

●     Technical Leadership: Demonstrated ability to lead data engineering projects and promote best practices across the team.

 

Qualifications:

●     Minimum of 5 years of experience in data engineering, data modeling, and analytics, with a strong focus on cloud-based environments.

●     Relevant certifications such as Google Cloud Professional Data Engineer, Google Cloud Professional Cloud Architect, or equivalent are highly desirable.

●     Experience in the retail industry or similar high-demand sectors is advantageous

●     Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field (nice to have, but not required)

 


Work Arrangement:

●     Fully Remote: This role is fully flexible and can be done remotely.

 

What We Offer:

An exceptional opportunity to be at the forefront of building a cutting-edge analytics infrastructure, playing a pivotal role in transforming our data capabilities. You will be part of a visionary team where innovation, technical excellence, and impact are valued and rewarded.

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