Celito - Technical Architect

Job Title: Technical Architect - Data Platform & Analytics (Life Sciences)

Employment Type: Full-time

Workplace Type: Remote

Timing: Upto 11 pm IST (Overlap with PST)

The Celito Team

The Celito Team architects the buildout of simplified, integrated, and compliant technology

stacks. With both consulting and products, our expertise can help our customers save time and

money as they move from strategic Clinical & Quality management all the way to widespread

and profitable commercialisation.

Job Overview

The Senior Data & Analytics Engineer / Technical Lead will serve as a key technical contributor

for designing, implementing, and supporting scalable enterprise data and analytics solutions

across AWS and/or Azure ecosystems. This role is responsible for leading hands-on engineering

activities across modern cloud-native data platforms, including data ingestion, transformation,

orchestration, reporting, and production support functions using technologies such as

Databricks, Snowflake, SQL, Python, and PySpark. The individual will collaborate closely with

architects, business stakeholders, analysts, and engineering teams to deliver scalable,

maintainable, and analytics-ready solutions while supporting DevOps, CI/CD, operational

excellence, and AI-enabled data initiatives across enterprise environments.

Responsibilities and Duties

Job Description

Design and implement scalable enterprise data and analytics solutions across AWS and/or

Azure ecosystems

Act as a hands-on technical lead contributing directly to architecture, engineering,

optimisation, troubleshooting, deployments, and production support activities

Build and maintain ingestion, transformation, orchestration, integration, API, and reporting

pipelines using modern cloud-native technologies, including Snowflake and Databricks

Design scalable enterprise data models, semantic/business layers, and analytics-ready data

structures for reporting and analytics platforms

Support analytics and reporting platforms, including Tableau, Power BI, and Spotfire

Support DevOps, CI/CD, deployment automation, release management, operational

support, and environment management processes

Manage production support activities, including monitoring, incident management, root

cause analysis, performance optimisation, and issue resolution

Support implementation of AI/ML and GenAI-enabled analytics solutions, reusable

frameworks, and AI-ready data platforms

Collaborate with architects, business stakeholders, analysts, and engineering teams to

deliver scalable and maintainable solutions

Contribute to technical standards, engineering best practices, documentation, governance,

and operational excellence initiatives

Qualifications

Bachelor's degree in computer science/software engineering or equivalent combination of

education and experience

8+ years of total IT experience

6+ years of hands-on experience designing and implementing Modern Data Platforms and

Analytics solutions

Experience working in Life Sciences, Pharma or MedTech domains

Strong hands-on expertise in SQL, Python, PySpark, and cloud-native data engineering

technologies

Job Description

Strong experience with Databricks, Snowflake, Redshift, Synapse, or similar modern data

platforms

Experience with AWS and/or Azure cloud services

Strong ETL/ELT, orchestration, pipeline development, API integrations, and performance

optimisation experience

Experience with Airflow, Step Functions, ADF, or similar orchestration technologies

Strong understanding of enterprise data modelling, dimensional modelling,

semantic/business layer modelling, and modern data warehousing concepts

Experience supporting enterprise reporting and dashboarding solutions using Tableau,

Power BI, Spotfire, or similar platforms

Experience with CI/CD, Git-based workflows, deployment automation, and operational

support activities

Strong troubleshooting, incident management, debugging, optimisation, and production

support capabilities

Good communication, collaboration, ownership, and technical leadership skills

Preferred Qualifications

Experience with Terraform, DevOps, and automation frameworks

Exposure to AI/ML, GenAI, LLMs, vector databases, or AI-enabled analytics solutions

Familiarity with AI-ready data platforms, RAG architectures, intelligent automation, or cloud

AI services