Data Architect

3 weeks ago


India SourceBae Full time
Job Title:

Solution Architect Lead Data Engineer

Experience: 10 - 15 Years

Contract/ Remote

About Us:

We are a leading technology service company that provides services in the field of data science, big data, enterprise cloud, and automation. As a forward-thinking company, we leverage cutting-edge technologies to drive innovation and enhance our business processes.

Role Overview:

We are seeking a talented and experienced data & AI engineer with strong Azure cloud competencies to join our dynamic team. The successful candidate will be responsible for delivering successful projects in customer environments, bringing use cases into production, machine learning projects, and large migrations.

Key Responsibilities:

  1. Architecture and Design: Establishing architecture and target design for data engineering and machine learning projects.
  2. Requirement Analysis: Current inventory analysis, review, and formalize requirements, project planning, and execution plan.
  3. Advisory Services: Troubleshooting, performance tuning, cost optimization, operational runbooks, and mentoring.
  4. Large Migrations: Assist customers with large migrations to Databricks from Hadoop ecosystems, data warehouses, ETL engines, SAS, SQL, DW, cloud-based data platforms like Redshift, Snowflake, EMR, etc.
  5. Design, Build, and Optimize Data Pipelines: The Databricks implementation will be best in class, with flexibility for future iterations.
  6. Production Readiness: Assisting with production readiness for customers, including exception handling, production cutover, capture analysis, alert scheduling, and monitoring.
  7. Machine Learning: Build and review ML models, ML best practices, model lifecycle, ML frameworks, and deploying models in production.

Must Have:

  • Hands-on experience with distributed computing framework like DataBricks, Spark-Ecosystem (Spark Core, PySpark, Spark Streaming, SparkSQL)
  • Willing to work with product teams to best optimize product features/functions.
  • Experience on Batch workloads and real-time streaming with high volume data frequency.
  • Performance optimization on Spark workloads.
  • Environment setup, user management, authentication, and cluster management on Databricks.
  • Professional curiosity and the ability to enable yourself in new technologies and tasks.
  • Good understanding of SQL and a good grasp of relational and analytical database management theory and practice.

Key Skills:

  • Python, SQL, and Pyspark
  • Big Data Ecosystem (Hadoop, Hive, Sqoop, HDFS, Hbase)
  • Spark Ecosystem (Spark Core, Spark Streaming, Spark SQL) / Databricks
  • Azure (ADF, ADB, Logic Apps, Azure SQL database, Azure Key Vaults, ADLS, Synapse)
  • AWS (Lambda, AWS Glue, S3, Redshift)
  • Data Modelling, ETL Methodology

Requirements:

The ideal candidate will have strong skills in implementation, data governance, data modeling, presales, AWS, and Databricks. They should also be able to lead a team at an Architect level.

How to Apply:

Interested candidates should submit their CV via email or share it via WhatsApp at the company's designated contact information.

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