Data Solution Engineer/Architect

As a Data Solution Engineer/Architect Advanced Analytics within our professional services practice, you will lead the design and delivery of cloud-native analytics architectures that solve complex data challenges for enterprise clients. This is a highly technical role that also requires strong consultative and business communication skills. You ll work directly with clients to assess needs, define modern analytics solutions, and lead implementation across the data lifecycle from ingestion and storage to reporting and machine learning. In addition to technical excellence, you ll play a key role in articulating the business value and ROI of these solutions, bridging the gap between IT and strategic business outcomes.

Key Responsibilities:

Lead the architecture of scalable, secure, and cost-efficient data platforms on cloud infrastructure (AWS, Azure, Google Cloud Platform).

Collaborate with client stakeholders to define business goals and map them to technical capabilities and solution designs.

Design and implement robust data pipelines (batch and streaming), modeling strategies, and analytics workflows using modern toolchains.

Guide the selection and integration of data warehousing, lakehouse, and visualization platforms.

Present architectural proposals and technical recommendations to client leadership, emphasizing expected business impact and measurable outcomes (e.g., faster time-to-insight, reduced data ops overhead, improved data quality).

Translate technical trade-offs into business terms to help clients make informed decisions.

Support clients in aligning analytics architectures with KPIs, compliance requirements, and digital transformation goals.

Participate in sales support activities such as technical scoping, RFP responses, demos, and solution architecture documentation.

Act as a mentor to consultants and data engineers, ensuring best practices are followed throughout implementation.

Technical Stack (Experience Preferred):

Cloud Platforms: AWS (Redshift, Glue, EMR), Azure (Synapse, Data Factory), Google Cloud Platform (BigQuery, Dataflow)

Data Engineering: dbt, Spark, Airflow, Databricks, Snowflake, Delta Lake, Data Vault, Canonical Data Model

Streaming: Kafka, Kinesis, Event Hubs

Storage & Warehousing: S3, ADLS, BigQuery, Synapse, Snowflake

Programming: SQL (advanced), Python, PySpark

BI/Visualization: Power BI, Tableau, Looker

Infra & DevOps: Terraform, Docker, Kubernetes, CI/CD (GitHub Actions, Azure DevOps)

Security & Governance: IAM, RBAC, encryption, compliance (HIPAA, SOC 2, GDPR)

Required Qualifications:

Bachelor s degree in Computer Science, Data Engineering, or a related technical discipline.

7+ years of experience in data and analytics, with 3+ years in a lead or architect role.

Proven ability to design and implement complex analytics platforms and data ecosystems.

Demonstrated experience communicating technical concepts to business audiences, with an emphasis on value realization and impact.

Background in consulting or professional services with client-facing responsibilities.

Preferred:

Master s degree in a technical or data-focused discipline.

Certifications in AWS, Azure, or Google Cloud Platform (architect or data engineering tracks).

Experience aligning analytics initiatives with business strategies like digital transformation, customer 360, or operational optimization.

Exposure to MLOps and integration of ML models into data pipelines.