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.

Skills Required

Tableau, Sql, Airflow, Data Modeling, dbt, Devops, MLops, Power Bi, Aws, Python, Kubernetes, Azure, Docker, Gcp