Data Engineer

An organization building data-driven products is looking for a

Data Engineer

who enjoys turning complex data into reliable, scalable systems. The role focuses on building data pipelines, managing large datasets, and ensuring clean, accessible data for analytics and product teams. This position is suited for engineers who like working with

modern data stacks, cloud infrastructure, and large-scale datasets . Key Responsibilities Build and maintain scalable

data pipelines and ETL/ELT workflows Design and optimize

data models, data lakes, and data warehouses Work with engineering and analytics teams to ensure

data quality and reliability Process and transform

large structured and unstructured datasets Monitor and improve

pipeline performance and system stability Implement

data validation, governance, and security practices Support data availability for

analytics, reporting, and machine learning use cases Skills & Experience Strong experience with

Python and SQL Hands-on experience building

ETL pipelines Experience with

cloud platforms (AWS, GCP, or Azure) Familiarity with

data warehouses such as Snowflake, BigQuery, or Redshift Experience working with

distributed data processing tools (Spark, Kafka, or similar) Understanding of

data modeling and data architecture Experience with

workflow orchestration tools (Airflow, Prefect, etc.) Nice to Have Experience working with

real-time data pipelines Familiarity with

data governance and quality frameworks Exposure to

ML data pipelines or analytics platforms Why This Role Work on

large-scale data systems Opportunity to build

foundational data infrastructure Collaborate with engineering, product, and analytics teams Solve meaningful problems using data Apply Now If building reliable data systems and scalable pipelines sounds exciting, this role could be a great fit.