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Data Engineering Solutions Architect
2 weeks ago
Job Title: Data Engineering Solutions Architect Location: Job Type: Full-time 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, and reporting solutions across modern and traditional data platforms. You will play a key role in defining scalable, secure, and cost-effective architectures that enable advanced analytics and AI-driven insights for our clients. 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. 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 . # Define and implement data ingestion, transformation, integration and orchestration frameworks for structured and semi-structured data. # Architect data lakes and data warehouses with an emphasis on scalability, cost optimization, performance, and governance. # Support real-time and API-based data integration scenarios; Lead design and delivery of data visualization and reporting solutions using tools such as Power BI, Tableau, and Streamlit . # Establish and enforce engineering standards, frameworks, and reusable assets to improve delivery efficiency and solution quality. # Mentor data engineers and help build internal capability on emerging technologies. # Provide thought leadership around modern data platforms, AI/ML integration, and data modernization strategies . 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.) 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). ~ 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 . Work on cutting-edge data and AI engagements with global clients. Collaborate with a team of passionate, high-performing data professionals. Culture that values innovation, continuous learning, and career growth . Competitive compensation and benefits package. Logic Pursuits provides companies with innovative technology solutions for everyday business problems. Our passion is to help clients become intelligent, information-driven organizations, where fact-based decision-making is embedded into daily operations, leading to better processes and outcomes. Our team combines strategic consulting services with growth-enabling technologies to evaluate risk, manage data, and leverage AI and automation more effectively. With deep big four consulting experience in business transformation and efficient processes, Logic Pursuits is a game-changer in any operations strategy .
