19 Oct
Shop Suki
Rajahmundry
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.
▶️ Data Analytics Engineer
🖊️ Shop Suki
📍 Rajahmundry