Data Engineer - AI Solutions

Siemens

4 - 9 years

3 - 11 Lacs

Bengaluru Karnataka India

Posted:2 weeks ago| Platform: Foundit logo

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Skills Required

data manipulation tools data pipelines

Work Mode

On-site

Job Type

Full Time

Job Description

We are looking for

You'll make an impact by

Design, build, and maintain data pipelines that serve the needs of multiple stakeholders including software developers, data scientists, analysts, and business teams.
Ensure data pipelines are modular, resilient, and optimized for performance and low maintenance.
Collaborate with AI/ML teams to support training, inference, and monitoring needs through structured data delivery.
Implement ETL/ELT workflows for structured, semi-structured, and unstructured data using cloud-native tools.
Work with large-scale data lakes, streaming platforms, and batch processing systems to ingest and transform data.
Establish robust data validation, logging, and monitoring strategies to maintain data quality and lineage.
Optimize data infrastructure for scalability, cost- efficiency, and observability in cloud-based environments.
Ensure compliance with governance policies and data access controls across projects.

Use your skills to move the world forward!

Bachelor's degree in Computer Science, Information Systems, or a related field.
4+ years of experience designing and deploying scalable data pipelines in cloud environments.
Proficiency in Python, SQL, and data manipulation tools and frameworks (e.g., Apache Airflow, Spark, dbt, Pandas).
Practical experience with data lakes, data warehouses (e.g., Redshift, Snowflake, BigQuery), and streaming platforms (e.g., Kafka, Kinesis).
Strong understanding of data modeling, schema design, and data transformation patterns.
Experience working with AWS (Glue, S3, Redshift, Sagemaker) or Azure (Data Factory, Azure ML Studio, Azure Storage).
Familiarity with CI/CD for data pipelines and infrastructure-as-code (e.g., Terraform,
CloudFormation).
Exposure to building data solutions that serve AI/ML pipelines, including feature stores and real-time data ingestion.
Familiarity with observability, data versioning, and pipeline testing tools.
Experience engaging with diverse stakeholders, gathering data requirements, and supporting iterative development cycles.
Background or familiarity with the Power, Energy, or Electrification sector is a strong plus.
Knowledge of security best practices and data compliance policies for enterprise-grade systems.

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