Lead Data Engineer Spectrum Talent Management

7.0 - 12.0 years

20 - 30 Lacs

bengaluru

Hybrid

Key Result Area: 1. Create and maintain optimal data pipeline architecture. 2. Assemble large, complex data sets that meet functional / non-functional business requirements. 3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. 4. Build the infrastructure required for optimal extraction, transformation and loading of data from a wide variety of data sources using SQL, Snowflake and AWS technologies. 5. Build analytics tools that utilize the data pipeline to provide actionable insights from business/financial products dataset, operational efficiency and other key business performance metrics. 6. Work with stakeholders including the Executive, Product, Data and Finance teams to assist with data-related technical issues and support their data infrastructure needs. 7. Work with data and analytics experts to strive for greater functionality in our data systems. Required Experience: 1. Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. 2. Experience building and optimizing big data’ data pipelines, architectures and data sets. 3. Strong analytic skills related to working with unstructured datasets. 4. Build processes supporting data transformation, data structures, metadata, dependency and workload management. 5. Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. 6. Knowledge of designing and implementing efficient data models and architecture. 7. We are looking for a candidate with 7-10 years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Information Systems or another quantitative field. They should also have experience using the following software/tools: Experience with big data tools: Snowflake, Spark, Kafka etc. Experience with relational SQL and NoSQL databases Experience with AWS cloud services: EC2, EMR, RDS, Redshift Experience with object-oriented/object function scripting languages: Python

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