About this role
Role Overview
The Specialist - Data Analytics is a high-impact technical role focused on the core engineering and optimization of our data environment. You will serve as the subject matter expert (SME) for data warehousing, responsible for building the robust infrastructure that enables data-driven decision-making across the organization. This role requires a "Growth Mindset" to constantly improve legacy systems and a deep technical mastery of SQL, Python, and AWS.
Key Responsibilities
Data Warehouse Engineering: Design and implement scalable data warehouse solutions that serve as the foundation for enterprise analytics.
Advanced Query Optimization: Develop and refine complex SQL scripts for data extraction and transformation, ensuring maximum performance and minimal latency.
ETL & Automation: Build and maintain automated data pipelines using Python to streamline the movement and processing of large datasets.
AWS Infrastructure Management: Effectively utilize AWS cloud services to optimize data storage, compute resources, and overall analytics performance.
Cross-Functional Technical Partnership: Collaborate with teams to understand business requirements and translate them into efficient data models and technical workflows.
Data Security & Integrity: Implement and monitor rigorous data security protocols and performance tuning to ensure the reliability of our data assets.
Professional Qualifications
Experience: 5–7 years of intensive experience in Data Warehousing and Analytics, with a track record of delivering high-performance data solutions.
Education: Degree in Computer Science, Information Technology, Data Science, or a related field.
Cloud Expertise: Practical, hands-on experience deploying data solutions within the AWS ecosystem (Redshift, S3, Glue).
Execution Focus: Proven ability to manage complex technical projects independently while maintaining alignment with global stakeholders.
Technical Skill Inventory
SQL Mastery: Expert-level proficiency in SQL, including advanced stored procedures, indexing strategies, and query performance tuning.
Python for Data: Strong experience using Python for ETL automation, data cleaning, and processing.
Data Architecture: In-depth knowledge of data modeling (Star/Snowflake schemas) and warehouse design principles.
ITSM Awareness: Understanding of how data performance impacts end-user experience and business SLAs.
BI & Reporting (Good to Have): Hands-on experience with Power BI or Tableau to visualize complex data trends.
At Freshworks, we have fostered an environment that enables everyone to find their true potential, purpose, and passion, welcoming colleagues of all backgrounds, genders, sexual orientations, religions, and ethnicities. We are committed to providing equal opportunity and believe that diversity in the workplace creates a more vibrant, richer environment that boosts the goals of our employees, communities, and business. Fresh vision. Real impact. Come build it with us.