The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. He/she must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, he/she must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates and supervisors.
Process Manager Role and responsibilities:
- Write efficient, production-grade Python scripts for data extraction, transformation, and automation tasks.
- Design and optimize SQL queries to analyze large, complex datasets across multiple sources (Presto Server, Hive, Spark, etc.).
- Develop and maintain reusable ETL pipelines using Python libraries such as pandas, sqlalchemy, or Airflow or any tools available at client disposal.
- Willingness to learn any new ETL tool as per the client requirements.
- Client-Facing Ownership
- Lead weekly or bi-weekly calls with clients, understand their analytical needs, and translate them into actionable data tasks.
- Present insights and dashboards in a structured, business-friendly manner using tools like Tableau, Power BI, or Google Data Studio.
- Manage project timelines, expectations, and delivery quality for 1–3 active clients simultaneously.
- Contribute to standardizing and documenting reusable scripts and SQL templates.
- Collaborate effectively with internal teams and client SPOCs to deliver end-to-end solutions.
- Ensure data accuracy, integrity, and compliance during data handling and reporting.
Technical and Functional Skills:
- 5+ years of experience in data roles involving Python and SQL in production environments.
- 2–3 years of direct client interaction, ideally in a services or consulting setup.
- Strong problem-solving skills with measurable outcomes from past projects (e.g., improved reporting efficiency by X%, reduced data processing time by Y%).
- Excellent communication, both verbal and written, with the ability to translate complex data into business insights.
- Experience working with cloud data platforms (e.g., AWS, GCP).
- Familiarity with project management tools (e.g., JIRA, Asana).
- Exposure to APIs and data integrations using REST.
- Knowledge of data modeling and performance tuning.