Data Engineer II

1 week ago

Delhi, India Talentoj Full time
Role Purpose:The Data Engineer II will play a crucial role in enhancing the data infrastructure and analytics capabilities. This role is vital for building and maintaining data transformation pipelines, monitoring data distribution shifts, managing dataset versions, and analyzing system performance. Contributions in this position will support the continuous improvement of machine learning models, ensuring they operate with high accuracy and efficiency in various production environments.

Role Value:As a Data Engineer II, you will be instrumental in advancing data engineering processes and infrastructure. Your expertise in building data pipelines, managing datasets, and analyzing system performance will directly impact the efficiency and reliability of machine learning models. By automating data transformation processes and monitoring data distribution shifts, you will help ensure that models are frequently updated and operate effectively in production.

T-Shaped Engineering Expectation:Beyond deep expertise in data engineering, you will bring a broad understanding of software development, testing, and data science. As a T-shaped Data Engineer, you will take full ownership of the data infrastructure you build, ensuring it is reliable, thoroughly tested, and capable of supporting machine learning and analytics efforts. Your skills in Python, SQL, and cloud environments will enable you to tackle complex data challenges, provide valuable insights into system behavior, and contribute to delivering top-tier identity verification solutions. Your work will play a critical role in maintaining leadership in the online identity verification, eKYC, and AML solutions market.

Example Responsibilities:Building data transformation pipelines with humans in the loop:

Automate and expand a semi-manual datasets generation pipeline, including tagging jobs preparation, scheduling, and post-processing to increase the frequency of ML model updates.Data distribution shift monitoring:

Design a system capable of detecting changes in data distribution and unknown data types by monitoring ML models in production.Dataset growth strategy:

Leverage your expertise in business data and monitoring tools to help identify valuable zones of expansion for automated solutions.Dataset versioning management:

Manage and document dataset versions in an ecosystem of highly dependent and evolving datasets.Data volatility management:

Develop solutions to stabilize datasets in environments where data retention is time-limited.System performance analysis:

Dive into data and models to analyze system behavior on specific transactions and data buckets, producing targeted performance metrics using advanced Python skills.

Experience and Qualifications:Experience building data pipelines in dynamic and evolving environments.Proficiency in Python (pandas, numpy) and SQL for data wrangling.Skilled in data analysis and deep dives using Jupyter notebooks or other notebook tools.Interest or experience in Machine Learning and Data Science.Proficient in leveraging cloud environments.

Great-to-Have Experience and Qualifications:Familiarity with privacy by design.Knowledge of serverless data engineering.Experience with Java, Apache Spark, or Flink.

Work Environment:Located in a hub of technical excellence with a strong focus on Machine Learning enablement, the team is committed to high standards, innovation, and continuous learning.

Values:IDEAL:

Integrity, Diversity, Empowerment, Accountability, Leading Innovation

Equal Opportunities:We foster a collaborative environment of diverse perspectives and backgrounds, welcoming applications and colleagues from all walks of life.

About Us:We are a B2B technology company dedicated to eradicating online identity fraud, money laundering, and other financial crimes, working to make the internet a safer space. Through AI, biometrics, machine learning, liveness detection, and automation, we create solutions trusted by global brands across Financial Services, Travel, Sharing Economy, Fintech, Gaming, and other industries.

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