Data Analytics Lead Engineer

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

Qualifications:

Required:

• 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 GCP (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