Data Platform Architect

4 weeks ago

Pune, India Enlighten HR Consulting Full time
Job Title: Lead Data Engineer

We are seeking an experienced Lead Data Engineer to join our team and lead the development of a cutting-edge data platform. The platform will leverage distributed computing frameworks such as Apache Spark, Databricks, and Snowflake to enable near real-time supply chain planning, eventually leading to advanced analytics and insights into data with the adoption of Generative AI (GenAI) technologies across our product base.

Key Responsibilities:
  • Design and build a highly scalable, fault-tolerant data platform optimized for distributed computing and large-scale data processing.
  • Implement data pipelines and ETL/ELT processes using distributed computing frameworks to efficiently ingest, transform, and load massive datasets from various sources.
  • Leverage cloud data platforms to enable seamless data sharing, near-zero maintenance, and fast analytics on structured and semi-structured data.
  • Collaborate with data scientists, machine learning engineers, and software developers to understand data requirements and build solutions to power GenAI applications.
  • Optimize distributed computing jobs and queries for maximum performance and cost efficiency.
  • Implement data governance, security, and compliance best practices.
  • Provide guidance on distributed computing architecture and mentor junior data engineers.
Qualifications:
  • 5+ years of experience as a Data Engineer working with big data technologies.
  • Strong proficiency in SQL, Python programming, and data modeling techniques.
  • Deep expertise in distributed computing principles and frameworks (e.g., Apache Spark), including SQL, streaming, and optimizing jobs for scale and efficiency.
  • Hands-on experience with developing and deploying distributed computing applications using cloud-based platforms (e.g., AWS EMR, Azure HDInsight, or equivalent).
  • Strong understanding of cloud data platform architectures and best practices for ELT/ETL, data sharing, and query optimization (e.g., AWS Athena, AWS Glue, Azure Synapse Analytics, or equivalent).
  • Experience enabling application engineers to build applications leveraging the data platform through APIs and abstractions.
  • Experience with orchestration frameworks like Apache Airflow and data streaming technologies like Kafka.
  • Experience building and optimizing data pipelines for machine learning applications.
  • Knowledge of data modeling, data warehousing, and schema design.
  • Familiarity with public cloud platforms such as AWS, Azure, or GCP.
  • Excellent problem-solving and communication skills.
  • Bachelor's or Master's degree in Computer Science (Preferred), Engineering, or a related field.

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