Data Engineer

Tarento Technologies

3 - 5 years

7 Lacs

bengaluru

Posted:2 weeks ago| Platform:

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Skills Required

product engineering manager quality assurance data structures healthcare data processing data quality apache business intelligence analytics monitoring

Work Mode

Work from Office

Job Type

Full Time

Job Description

About Tarento

Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare. Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions.

Were proud to be recognized as a Great Place to Work

, a testament to our inclusive culture, strong leadership, and commitment to employee well-being and growth. At Tarento, you ll be part of a collaborative environment where ideas are valued, learning is continuous, and careers are built on passion and purpose.

Primary Skill/Mandatory Skill/Must Have

Data Pipeline Development:
Design, build, and maintain scalable and reliable data pipelines using
Apache Spark
,
Kafka
, and
Apache Flink
for real-time data processing and large-scale batch data workflows.
Real-time Data Streaming:
Implement and manage real-time data streaming architectures leveraging
Apache Kafka
to process and transmit high volumes of streaming data in a fault-tolerant manner.
Data Transformation and Orchestration:
Develop data transformation workflows and integrate data from various sources while ensuring that pipelines are robust, efficient, and adhere to
data engineering best practices
.

Good to have

Data Quality Assurance:
Implement data validation, quality checks, and monitoring systems to ensure data integrity and consistency across the entire data pipeline.
Collaboration with Cross-functional Teams:
Work closely with Data Scientists, Analysts, and other stakeholders to understand data requirements and provide reliable data infrastructure solutions.
Performance Optimization:
Continuously monitor and optimize data processing performance, focusing on scaling solutions and improving efficiency.
Documentation & Best Practices:
Maintain clear documentation for data pipelines, data structures, and processes. Advocate for industry-standard data engineering practices across the team.
Tool Expertise:
Leverage tools like
Looker
for Business Intelligence (BI) and
BigQuery (BQ)
for data warehousing to support analytics and decision-making processes.

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