Job Description

Title:

Data Engineering Solutions Architect

---------------------------------------------------

Experience:

8-12 Years

Location:

Hyderabad

Mandatory Skills

Data Architecture Snowflake dbt Matillion Python AWS / Azure / GCP Medallion Architecture

We are looking for an experienced

Data Engineering Solutions Architect

to join our growing Data Practice. The ideal candidate will have

8-12 years of hands-on experience

designing, architecting, and delivering large-scale

data warehousing, data lake, ETL/ELT, and reporting solutions

across modern and traditional data platforms.


You will play a key role in defining

scalable, secure, and cost-effective data architectures

that enable advanced analytics and AI-driven insights for our clients. This role demands a strong mix of

technical depth, solution leadership, and a consulting mindset

.

Key Responsibilities

Design and architect end-to-end data solutions using

Snowflake, Databricks, dbt, Matillion, Python, Airflow, Control-M

, and cloud-native services across

AWS, Azure, and GCP

. Build and manage data ingestion, transformation, integration, and orchestration frameworks for structured and semi-structured data. Architect scalable

data lakes and data warehouses

with focus on performance, governance, and cost optimization. Design solutions for

real-time, streaming, micro-batch, and event-driven

ingestion patterns. Lead delivery of

data visualization and reporting

using

Power BI, Tableau, and Streamlit

. Work closely with business and technical stakeholders to translate requirements into architecture blueprints. Define and enforce engineering standards, reusable frameworks, and delivery best practices. Mentor data engineers and support capability building on emerging technologies. Provide thought leadership on

data modernization, AI/ML enablement, and platform strategy

.

Required Qualifications

8-12 years of experience in

Data Engineering / Data Architecture

with hands-on delivery experience. Strong expertise in

Snowflake or Databricks

; hands-on with

SQL, Python/PySpark, dbt, and Matillion

. Experience building and orchestrating pipelines with

Airflow, Control-M

, or similar tools. Experience with cloud-native services such as

AWS Glue, Redshift, Athena

,

GCP BigQuery, Dataflow, Pub/Sub

, or equivalent. Strong knowledge of

data modeling, ETL/ELT design

, and

Medallion / layered / modular architectures

. Experience with

real-time and API-based integrations

such as

Kafka, Kinesis, Pub/Sub, and REST APIs

. Familiarity with traditional ETL tools like

Informatica, SSIS, and Oracle Data Integrator

. Strong understanding of

data governance, performance tuning, and Data DevOps (CI/CD)

. Excellent communication and stakeholder management skills.

Preferred Qualifications

Certifications:

Snowflake SnowPro

,

Databricks Certified Architect

,

AWS Data Analytics Specialty

,

Google Professional Data Engineer

. Consulting or client-facing experience. Exposure to

AI/ML frameworks, data quality, or metadata management

. * Experience in

multi-cloud or hybrid architecture design

.