Data Lakehouse/Platform Architect

Experience: 12-18 years

Job Overview:

We are seeking an experienced Data Lakehouse/Platform Architect to join our consultingteam. In this role, you will be responsible for working closely with our clients to design,architect, and build data lakehouses or data platforms. These platforms will enable data scienceand analytics teams to leverage data for AI model development, analytics, and reporting.The ideal candidate should have deep technical expertise in data architecture, cloud platforms,and big data technologies, along with a strong consulting background. You will guide customersthrough the process of building scalable and efficient data ecosystems that align with theirbusiness objectives and data science goals.

Key Responsibilities:

Consult with clients to understand their business and technical needs, and designscalable, high-performance Data Lakehouse/Data Platform solutions. Define and deliver a clear roadmap for data lakehouse implementations, ensuringalignment with client goals in data analytics, AI, and machine learning. Architect and design data ingestion, storage, transformation, and governance solutions,leveraging modern data lakehouse technologies (e.g., Delta Lake, Apache Iceberg,Apache Hudi). Lead customer engagements on cloud-based data platform strategies across AWS,Azure, or GCP, and provide guidance on data management best practices. Develop ETL/ELT pipelines for structured and unstructured data, enabling Data Scienceand BI teams to efficiently access and process data. Ensure data security, governance, and compliance throughout the data lifecycle. Collaborate with client teams, internal stakeholders, and external partners to executeend-to-end data platform implementation projects. Conduct technology assessments, evaluate emerging tools, and recommend best-fitsolutions based on client requirements. Provide mentoring, training, and thought leadership to client and internal teams on DataLakehouse architecture, data modeling, and data pipeline best practices.

Required Qualifications:

Proven experience (7+ years) in data architecture, data engineering, or data platformroles with a focus on building scalable data solutions. Expertise in modern data lakehouse architecture, including tools like Apache Spark,Delta Lake, Snowflake, BigQuery, or similar. Hands-on experience with cloud platforms (AWS, Azure, GCP) and their data services,such as AWS S3, Azure Data Lake, or GCP BigQuery. Strong understanding of ETL/ELT pipeline design, orchestration frameworks (e.g.,Airflow, dbt), and data modeling principles. Proficient in distributed computing and data processing frameworks (e.g., Hadoop,Spark, Presto, etc.). Knowledge of data governance, security best practices, and compliance regulations(GDPR, HIPAA, etc.). Strong consulting skills with the ability to assess client requirements, develop technicalstrategies, and provide value-driven recommendations. Excellent communication, presentation, and interpersonal skills to work with bothtechnical and business teams.Preferred Qualifications: Familiarity with AI/ML model development lifecycle and data science workflows. Experience with streaming data platforms (Kafka, Kinesis, etc.). Certification in cloud platforms (AWS, Azure, GCP).