Pune, Maharashtra, India
Information Technology
Full-Time
Pocketpills
Overview
We are looking for a dynamic and hands-on Data Analytics & AI professional to join our growing team. The ideal candidate will have a strong foundation in SQL and Python, experience with modern data engineering practices, and the ability to lead analytics initiatives while guiding junior team members. This role requires someone who can work in a fast-paced, evolving environment, handle ambiguity, and work directly with leadership to drive data-informed decisions.
Responsibilities
Responsibilities
- Design, build, and maintain data pipelines and analytical workflows following data engineering best practices.
- Work on exploratory data analysis, business intelligence, and AI/ML-oriented problem-solving.
- Use data visualization tools to build dashboards and reports for decision-making.
- Collaborate directly with stakeholders and leadership to understand and translate business requirements into analytics and data solutions.
- Mentor and support junior analysts on the team.
- Proactively adapt to changing business needs and adjust analytical approaches accordingly.
- Be available for PST time zone meetings while working in the IST time zone.
- 4-5 years of experience in data analytics, data engineering, or related fields.
- Strong proficiency in SQL and Python for data manipulation and analysis.
- Hands-on experience in designing and building data pipelines and working with large-scale datasets.
- Familiarity with data engineering best practices like modular code, documentation, version control(GIT), and testing.
- Experience with at least one data visualization tool (Tableau, Redash, Power BI, etc. ).
- Excellent communication skills and ability to work directly with leadership and cross-functional teams.
- Ability to thrive in dynamic and fast-changing environments with minimal supervision.
- Strong analytical thinking with a bias for action and outcomes.
- Experience with tools such as Tableau, Redash, and Databricks.
- Background in working with e-commerce or customer-focused data products, or companies.
- Exposure to cloud data platforms (e. g., AWS, GCP, Azure).
- Experience working with ambiguous problem statements and hypothesis-driven analysis.
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