Data Engineer Solution Architect
Role summary
We are seeking an experienced Data Architect to design and lead the implementation of modern data platforms and analytics ecosystems. This role requires deep technical architecture capabilities and client-facing skills, as you will work closely with internal teams and external clients to define scalable data solutions. You will also support pre-sales initiatives by shaping solution architectures, participating in discovery workshops, and contributing to proposals and technical strategy discussions. Key responsibilities include architecting solutions using Databricks, Snowflake, and cloud environments (AWS, Azure, GCP), developing data pipelines, and establishing data governance standards.
Role Overview
We are seeking an experienced
Data Architect
to design and lead the implementation of modern data platforms and analytics ecosystems. The ideal candidate will have strong expertise in
Databricks, Snowflake, cloud-native data architectures across AWS, Azure GCP, as well as real-time streaming ecosystems.
This role requires both
deep technical architecture capabilities and client-facing skills
, as the candidate will work closely with internal engineering teams and external clients to define scalable data solutions. The Data Architect will also support
pre-sales initiatives
, helping shape solution architectures, participate in discovery workshops, and contribute to proposals and technical strategy discussions.
Key Responsibilities
1. Design and implement
modern data architectures
, including lakehouse and cloud data warehouse solutions using Databricks and Snowflake.
2. Define
end-to-end data platform architecture
covering data ingestion, processing, storage, governance, and analytics layers.
3. Architect and optimize data platforms across
AWS, Azure, and GCP cloud environments
.
4. Lead the development of
scalable ETL/ELT pipelines
using technologies such as Spark, Python, SQL, and orchestration tools.
5. Establish standards for
data modeling, data quality, security, and governance frameworks
.
6. Engage with clients during
pre-sales and solution discovery
, providing architecture guidance and participating in technical workshops.
7. Collaborate with sales teams to create
solution proposals, architecture diagrams, and effort estimates
for client opportunities.
8. Provide
technical leadership and architecture governance
to engineering teams throughout the project lifecycle.
Required Skills
1. 10+ years of experience in
data engineering, analytics platforms, or enterprise data architecture
.
2. Strong expertise in
Databricks (Spark, Delta Lake) and Snowflake data platform architecture
.
3. Hands-on experience across
AWS, Azure, and GCP cloud ecosystems
for building scalable data platforms.
4. Proficiency in
data pipeline development using Python, Spark, SQL, and orchestration tools such as Airflow or similar
.
5. Strong knowledge of
data modeling techniques (dimensional modeling, normalized models, data vault)
.
6. Experience designing
real-time and batch data processing architectures
, including streaming and CDC pipelines.
7. Ability to conduct
client workshops, architecture discussions, and technical presentations
during pre-sales engagements.
8. Excellent
communication and stakeholder management skills
, with the ability to translate business needs into technical solutions.
Preferred Qualifications
- Experience building
data accelerators or reusable platform frameworks
.
- Exposure to
AI/ML data pipelines and MLOps architectures
.
- Certifications in
Databricks, Snowflake, AWS, Azure, or GCP
at Professional category.
