Data Engineer
2 weeks ago
Job Description: Data Engineering I
Designation: Data Engineering I
Department: Technology
Location: Mumbai
Qualification: Engineering graduates
B.E/ B. Tech/ MCA/ M. Tech in computer science.
Platforms/Stacks/Tools/Languages:
Python, NoSQL, BigData, Cloud (AWS), Analytics, AI/ML, Data Engineering, MetaData
1. Experience:
- Bachelor & or master’s degree in analytics/engineering, computer science, or related field.
- 2+ years; experience as a data engineering position or similar role.
- Advanced working SQL knowledge and experience working with relational and nosql databases and query authoring (SQL)
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Should have strong experience in Tableau
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Excellent communication and presentation skills.
- Results-driven and able to handle multiple projects.
2. Key Roles and Responsibilities:
- Manage, enhance and establish best data engineering structure practices for the team.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Build analytics and engineering tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Apply statistics and data modelling to gain actionable business insights and boost customer productivity and revenue.
- Enforce company policies and procedures to ensure quality and prevent discrepancies.
- Communicate and track key performance metrics across departments.
- Identify business opportunities and ensure customer satisfaction.
- Manage cross-functional teams, review their performance, and manage schedules.
- Generate reports of findings and present these to senior management.
- Keep abreast of industry best practices and policies.
3. Key Expertise:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including MongoDB and MySql.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc.
About ShopSe: www.getshopse.com
ShopSe is focused on revolutionizing instant, paperless and cardless EMI solutions for consumers. We’re already in the league of top brands in our category and are raising the bar of the BNPL model. Affordability, Trust & Innovation is the backbone of our product. We’re backed by top VC firms, Chiratae Ventures (Formerly IDG Ventures India) & BeeNext in seed round. Featured in the hottest 30 start-ups in Inc42’s ‘30 Startups to Watch’.
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