Zensark Tecnologies Pvt Ltd

Data Engineer

Vaga remota de Data Engineering com fit claro de localização do candidato.

Publicada27 de jul. de 2026

Países elegíveis1 país aceito

Sinal de senioridadeSenior

Modelo de trabalhoRemoto

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Resumo da vaga

Conteúdo da vaga extraído em seções para revisão mais rápida.

Create and maintain optimal data pipeline architecture.
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater performance and 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 tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.

5+ years of experience in a Data Engineer role
Experience with relational SQL and NoSQL databases, including Postgres, Oracle and Cassandra.
Experience with data pipeline and workflow management tools.
Experience with AWS cloud services: S3, EC2, EMR, RDS, Redshift.
Experience with stream-processing systems: Storm, Spark-Streaming, Amazon Kinesis, etc.
Experience with object-oriented/object function scripting languages: Python, Java, NodeJs.
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
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 both structured and 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.
Strong project management and organizational skills.
Experience supporting and working with cross-functional teams in a dynamic environment.