We are looking for a Mid-Level Data Engineer to design, build, and maintain scalable data pipelines and data platforms that support analytics, reporting, and machine learning use cases. You will work closely with data analysts, data scientists, and software engineers to ensure reliable, high-quality data across the organization.
This role is ideal for someone with solid hands-on experience who can own data pipelines end-to-end and contribute to improving our data architecture.
Key Responsibilities-
Design, build, and maintain ETL/ELT pipelines that ingest data from multiple sources
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Develop and optimize data models for analytics and reporting use cases
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Ensure data quality, reliability, and performance across pipelines
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Work with stakeholders to understand data requirements and translate them into technical solutions
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Optimize data storage and query performance in data warehouses and/or data lakes
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Monitor pipelines and troubleshoot data issues in production
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Write clean, maintainable, and well-documented code
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Collaborate with DevOps and engineering teams on deployment, scaling, and security best practices
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3–5 years of experience in Data Engineering or a related role
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Strong proficiency in SQL and at least one programming language (Python preferred)
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Hands-on experience with ETL/ELT tools or frameworks (e.g., Airflow, dbt, Spark)
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Experience working with data warehouses (e.g., Snowflake, BigQuery, Redshift)
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Familiarity with cloud platforms (AWS, GCP, or Azure)
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Understanding of data modeling concepts (star schema, normalization, denormalization)
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Experience with version control systems (Git)
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Experience with streaming data (Kafka, Kinesis, Pub/Sub)
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Knowledge of CI/CD pipelines for data workflows
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Exposure to machine learning data pipelines
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Familiarity with data governance, security, and compliance practices
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Strong problem-solving and analytical skills
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Ability to work independently and manage priorities
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Clear communication with both technical and non-technical stakeholders
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Team-oriented mindset with attention to detail
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Competitive salary and benefits
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Flexible working arrangements
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Opportunities for learning and career growth
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Collaborative and data-driven culture