Lead Assistant Manager

Role Overview

We are seeking a versatile Data & Analytics Specialist who can work across the full spectrum of data capabilities-ranging from data engineering and pipeline management to business intelligence, advanced analytics, and operational excellence. This role is ideal for individuals who thrive in cross-functional environments, bridging the gap between data platforms, business teams, and operations.

Key Responsibilities

Business Intelligence (BI)

• Build, maintain, and optimize dashboards, reports, and self-service analytics solutions.

• Translate business requirements into meaningful KPIs and data visualizations.

• Partner with stakeholders to enable data-driven decision-making.

Data Engineering (DE)

• Design and maintain scalable ETL/ELT pipelines and data models.

• Ensure high-quality, clean, and reliable data is available for downstream use.

• Manage data warehouse / lakehouse platforms (e.g., Snowflake, BigQuery, Redshift, Databricks).

Data Science (DS)

• Apply machine learning/statistical models to solve business problems.

• Develop predictive models (e.g., customer behavior, forecasting, anomaly detection).

• Work on model deployment and monitoring in collaboration with Ops/Engineering.

Operations (Ops)

• Ensure smooth functioning of data pipelines and analytics infrastructure.

• Implement monitoring, alerting, and logging for data workflows and ML models.

• Support CI/CD processes, automation, and scalability for data products.

Required Skills & Experience

• Technical Skills

  • Strong SQL and data modeling skills.

  • Hands-on with Python/R for analytics and ML.

  • Experience with cloud data platforms (AWS, Azure, or GCP).

  • Familiarity with data orchestration tools (Airflow, dbt, Prefect).

  • Visualization tools: Power BI, Tableau, or Looker.

• Analytical Skills

• Ops Skills

• Collaboration Skills

Qualifications

• Bachelor's or Master's in Computer Science, Data Science, Statistics, Engineering, or related field.

• 3-7 years of hands-on experience across BI, DE, DS, or Ops roles (breadth over depth is valued).

• Strong problem-solving mindset with end-to-end ownership of data products.