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The Data Engineer will play a critical role in the data modernization project by focusing on the design, automation, and optimization of ETL pipelines. This role will primarily involve ensuring seamless integration with Snowflake and PostgreSQL and implementing robust data transformation workflows. The Data Engineer will collaborate closely with the Airflow Specialist and the Data Architect to maintain alignment with the overall data architecture while focusing on delivering high-performance data pipelines. Responsibilities and Duties 1. ETL Pipeline Development & Automation: - Design, develop, and automate ETL pipelines to migrate data from legacy systems to modern platforms. - Leverage tools such as AWS Glue, dbt, and Python to support data ingestion, transformation, and integration. - Maintain high-quality, scalable pipelines capable of processing large datasets efficiently. 1. Data Transformation & Integration: - Implement data transformation workflows to prepare data for analytical workloads in Snowflake and PostgreSQL environments. - Ensure data consistency and integrity during transformations by leveraging best practices in schema enforcement and validation. 1. Collaboration & Alignment: - Work closely with the Airflow Specialist to align ETL workflows with orchestration pipelines. - Collaborate with the Data Architect to ensure data models and pipelines align with overall system design and project goals. 1. Process Optimization: - Identify opportunities for optimizing ETL processes to enhance performance and reduce costs. - Implement change data capture (CDC) mechanisms and incremental updates to ensure timely data availability. 1. Data Quality & Monitoring: - Support the integration of automated validation tools, such as Great Expectations, into ETL workflows. - Monitor ETL processes to ensure consistent performance and timely issue resolution. Qualifications and Skills - 8+ years of experience in data engineering, with a focus on building and automating ETL pipelines. - Hands-on expertise with AWS Glue, Python, and dbt for data transformation and pipeline development. - Proven experience integrating data workflows into Snowflake and PostgreSQL. - Strong understanding of modern data architecture principles and ETL best practices. - Familiarity with data governance tools such as DataHub and validation frameworks like Great Expectations. - 5+ years of experience in data engineering, with a focus on building and automating ETL pipelines. - Hands-on expertise with AWS Glue, Python, and dbt for data transformation and pipeline development. - Proven experience integrating data workflows into Snowflake and PostgreSQL. - Strong understanding of contemporary data architecture principles and ETL best practices. - Familiarity with data governance tools such as DataHub and validation frameworks like Great Expectations. Additional Requirements - Experience with change data capture (CDC) and real-time data processing mechanisms. - Familiarity with Apache Spark for large-scale data transformation tasks. - Proficiency in integrating ETL workflows into Airflow orchestrations. - Strong analytical skills for identifying performance improvement opportunities in data workflows. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.