Lead Assistant Manager

Job Description: Data & Analytics Specialist (BI/DE/DS/Ops)

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: Ability to break down complex business problems into data solutions.

• Ops Skills: Understanding of DevOps/MLOps practices (CI/CD pipelines, monitoring, containerization with Docker/Kubernetes is a plus).

• Collaboration Skills: Ability to work with business, product, and tech stakeholders.

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.