Data Architect

Data Engineering Solutions Architect

Ideal Experience:

Location:

About the company (Our client)

A fast growing, boutique Data consulting firm that delivers innovative technology solutions designed to solve everyday business challenges. It focuses on enabling clients to become intelligent, information-driven enterprises where fact-based decision-making is seamlessly integrated into daily operations, resulting in stronger processes and improved outcomes. By combining strategic consulting expertise with growth-enabling technologies, the team helps organizations evaluate risk, manage data, and harness AI and automation more effectively.

About the Role

Data Engineering Solutions Architect

Key Responsibilities

Data Architecture & Engineering

• Design and architect end-to-end data solutions (Snowflake, Databricks, dbt, Matillion, Python, Airflow, Control-M).
• Build scalable data lakes and data warehouses with focus on performance, cost optimization, and governance.
• Define ingestion, transformation, orchestration, and integration frameworks for structured and semi-structured data.

Integration & Advanced Data Workflows

• Architect real-time, micro-batch, and event-driven data pipelines.
• Design API-based and streaming solutions (Kafka, Kinesis, Pub/Sub).
• Lead development of reporting and visualization solutions (Power BI, Tableau, Streamlit).

Consulting & Leadership

• Collaborate with business and technical stakeholders to shape architecture roadmaps.
• Establish engineering standards, reusable frameworks, and best practices.
• Mentor data engineers and support capability-building on emerging technologies.
• Provide thought leadership on data modernization, AI/ML integration, and next-gen data platforms.

Required Qualifications

• 8–12 years of hands-on experience in data engineering, architecture, and solution delivery.
• Strong expertise in

  Snowflake or Databricks

  , plus dbt, Matillion, SQL, Python/PySpark.
• Experience designing pipelines/orchestration using

  Airflow, Control-M

  , or similar tools.
• Working knowledge of cloud-native services (AWS Glue, Redshift, Athena; GCP BigQuery, Dataflow; Azure equivalents).
• Strong understanding of ELT/ETL, medallion/layered architectures, and data modelling.
• Experience with APIs, real-time ingestion, and streaming platforms.
• Familiarity with traditional ETL tools (Informatica, SSIS, ODI).
• Excellent communication, problem-solving, and stakeholder management skills.

Preferred Qualifications

• Certifications:
• Snowflake SnowPro
• Databricks Certified Architect
• AWS Data Analytics Specialty
• Google Professional Data Engineer
• Prior consulting or client-facing experience.
• Exposure to AI/ML, data quality, metadata management.
• Experience designing solutions across hybrid or multi-cloud environments.

Required Education

• B.E. / BCA / MCA / B.Tech. (or equivalent technical degree)

Why Join this company

• Work on cutting-edge data and AI programs with global clients.
• Join a high-performing, innovative data engineering team.
• Shape architectural strategy and influence technology direction.
• Strong learning culture with career growth opportunities.
• Competitive salary and benefits.