Description

You will lead the architecture of scalable, secure, and cost-efficient data platforms on cloud infrastructure.

Responsibilities

• Design and implement data pipelines for batch and streaming, including modeling strategies and analytics workflows.
• Collaborate with stakeholders to map business goals to technical solution designs and architectural proposals.
• Guide the selection and integration of data warehousing, lakehouse, and visualization platforms.
• Mentor consultants and data engineers to ensure technical best practices during implementation.
• Support sales activities including technical scoping, RFP responses, and solution architecture documentation.

Required Skills

• 7+ years of experience in data and analytics, with 3+ years in a lead or architect role.
• Advanced SQL and Python proficiency.
• Hands-on experience with PySpark and Spark.
• Expertise in Snowflake, Databricks, and Delta Lake.
• Experience with Airflow, dbt, and Data Vault or Canonical Data Modeling.
• Cloud platform experience including AWS (Redshift, Glue, EMR), Azure (Synapse, Data Factory), or GCP (BigQuery, Dataflow).
• Knowledge of streaming technologies like Kafka, Kinesis, or Event Hubs.
• Infrastructure and DevOps experience using Terraform, Docker, Kubernetes, and CI/CD.
• Background in consulting or professional services with client-facing responsibilities.

Preferred Skills

• Master’s degree in a technical or data-focused discipline.
• AWS, Azure, or GCP certifications in architect or data engineering tracks.
• Experience with MLOps and integrating ML models into data pipelines.

Key Skills

Education

Bachelor's or Master's degrees