Data Engineering Solutions Architect

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Job Type:

Data Engineering Solutions Architect

This role demands a balance of technical depth, solution leadership, and consulting mindset - helping customers solve complex data engineering challenges while also building internal capability and best practices within the organization.

Key Responsibilities

1. Design and architect

   end-to-end data solutions

   using technologies like

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

   , and cloud-native services on

   AWS/Azure/GCP

   .
2. Define and implement

   data ingestion, transformation, integration and orchestration frameworks

   for structured and semi-structured data.
3. Architect

   data lakes and data warehouses

   with an emphasis on scalability, cost optimization, performance, and governance.
4. Support

   real-time and API-based data integration

   scenarios; design solutions for streaming, micro-batch, and event-driven ingestion.
5. Lead design and delivery of

   data visualization and reporting

   solutions using tools such as

   Power BI, Tableau, and Streamlit

   .
6. Collaborate with business and technical stakeholders to define requirements, design architecture blueprints, and ensure alignment with business objectives.
7. Establish and enforce

   engineering standards, frameworks, and reusable assets

   to improve delivery efficiency and solution quality.
8. Mentor data engineers and help build internal capability on emerging technologies.
9. Provide thought leadership around

   modern data platforms, AI/ML integration, and data modernization strategies

   .

Required Qualifications

• 8–12 years of experience in

  data engineering and architecture

  , including hands-on solution delivery.
• Deep expertise with

  Snowflake or Databricks, with strong working knowledge of tools like dbt, Matillion, SQL, and Python or PySpark

  .
• Experience designing and implementing

  data pipelines and orchestration

  using tools like

  Airflow, Control-M, or equivalent

  .
• Familiarity with

  cloud-native data engineering services

  (Such as AWS Glue, Redshift, Athena, GCP BigQuery, Dataflow, Pub/Sub, etc.) or similar.
• Strong understanding of

  data modelling, ELT/ETL design, and modern architecture frameworks

  (medallion, layered, or modular architectures).
• Experience integrating and troubleshooting

  APIs and real-time data ingestion technologies

  (Kafka, Kinesis, Pub/Sub, REST APIs).
• Familiarity with

  traditional ETL and data integration tools

  (Informatica, SSIS, Oracle Data Integrator, etc.).
• Excellent understanding of

  data governance, performance tuning, and DevOps for data

  (CI/CD, version control, monitoring).
• Strong communication, problem-solving, and stakeholder management skills.

Preferred Qualifications

• Certifications such as:

• Snowflake SnowPro

  ,

  Databricks Certified Architect

  ,

  AWS Data Analytics Specialty

  , or

  Google Professional Data Engineer

  .
• Prior

  consulting or client-facing experience

  .
• Exposure to

  AI/ML, data quality, or metadata management frameworks

  .
• Experience leading solution design across

  multi-cloud or hybrid environments

  .

Why Join Us?

• Work on

  cutting-edge data and AI engagements

  with global clients.
• Collaborate with a team of passionate, high-performing data professionals.
• Opportunity to

  influence architecture strategy

  and build internal capability.
• Culture that values

  innovation, continuous learning, and career growth

  .
• Competitive compensation and benefits package.

About Us

Logic Pursuits is a game-changer in any operations strategy