Sr. Engineer II - Data Engg & AI

Anblicks; Hyderabad; On-site; INR 2,800,000 - 5,500,000; Full time

Job summary

Anblicks is seeking an experienced Data Modeler / Data Engineer with 8+ years of total experience to design scalable data models and ingestion architectures. The role requires strong SQL/RDBMS, dimensional modeling, and cloud data platform skills, with Snowflake knowledge considered a strong plus.

You will work across data modeling, Snowflake Medallion architecture implementation, and robust ETL/ELT pipeline development, collaborating with business analysts and data teams to deliver scalable,

Qualifications

• 8+ years total experience in data engineering and architecture.
• Minimum 5 years hands-on data modeling experience.
• Strong SQL and RDBMS skills; dimensional modeling (Kimball/Inmon).
• Experience with data warehousing, ETL/ELT, and cloud platforms (AWS).
• Knowledge of Snowflake data modeling is a plus.

Responsibilities

• Design and implement logical and physical data models for analytical and operational use cases.
• Build and maintain data ingestion layers (Bronze/Silver/Gold) for structured and semi-structured data.
• Develop optimized schemas and collaborate on robust ETL/ELT pipelines.
• Ensure data quality, lineage, and governance across data layers; document structures and transformations.

Skills

SQL & RDBMS

Dimensional Modeling

Data Warehousing

ETL/ELT

Cloud Platforms AWS

Lucidchart & ER Diagrams

Snowflake Data Modeling

DataOps concepts

Medallion Architecture

Tools

Lucidchart

ER Diagrams

Job description

Job Title - Data Modeler / Data Engineer

Location

Working hours: Ability to overlap at least 4–5 hours with U.S. Central Time for collaboration.

Role Overview

We are seeking an experienced Data Modeler/ Data Engineer with 8+ years of total experience and at least 5 years of hands‑on experience in implementing data modeling techniques and best practices. The candidate will design and implement scalable data models and ingestion frameworks using Medallion architecture. Strong technical skills in SQL, RDBMS, Dimensional Modeling (Kimball/Inmon), Data Warehousing, ETL/ELT, and Cloud Platforms are mandatory. Knowledge of Snowflake and IT Operations (ITOps) is a strong plus.

Key Responsibilities

Data Modeling

• Design and implement logical and physical data models for analytical and operational use cases.
• Apply data modeling techniques and best practices (dimensional modeling, normalization/denormalization, canonical modeling).
• Ensure models align with business requirements and support scalability and performance.

Snowflake Medallion Architecture Implementation

• Build and maintain data ingestion layers (Bronze, Silver, Gold) for structured and semi‑structured data.
• Define standards for data quality, lineage, and governance across layers.

Database & Pipeline Development

• Work with SQL and RDBMS systems to design optimized schemas.
• Collaborate with data engineering teams to implement robust ETL/ELT pipelines using modern orchestration tools.
• Apply DataOps principles for CI/CD, automated testing, and deployment of data workflows.

Collaboration & Documentation

• Work closely with business analysts and domain experts to translate requirements into data models.
• Maintain clear documentation for data structures, lineage, and transformation logic using tools like ER diagrams and Lucidchart.

Required Skills & Qualifications

• 8+ years of total experience in data engineering and architecture.
• Minimum 5 years of hands‑on experience in data modeling techniques and best practices.
• Strong technical skills in:
  • SQL and RDBMS
  • Dimensional Modeling (Kimball/Inmon)
  • Data Warehousing
  • ETL/ELT
  • Cloud Platforms (AWS)
  • Data Modeling Tools (ER diagrams, Lucidchart)
• Experience implementing Medallion architecture for data ingestion.
• Excellent communication skills and ability to work in a distributed team and stakeholder management.
• Knowledge of Snowflake Data Modeling will be an advantage.

Nice to Have

• Experience in the IT Operations (ITOps) domain (Monitoring & Telemetry, Incident Management & Ticketing, Cloud Cost & Billing, Managed Services SLA Data).
• Exposure to data governance and cataloging tools (Collibra, Soda).
• Knowledge of DataOps practices and pipeline orchestration tools.