Responsibilities

<ul>
<li style="margin-left:0px;">Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., Spark, Databricks, Airflow, Snowflake, etc.).</li>
</ul>

<ul>
<li style="margin-left:0px;">Develop ETL/ELT processes to ingest data from various structured and unstructured sources.</li>
</ul>

<ul>
<li style="margin-left:0px;">Perform Exploratory Data Analysis (EDA) to uncover trends, validate data integrity, and derive insights that inform data product development and business decisions.</li>
</ul>

<ul>
<li style="margin-left:0px;">Collaborate closely with data scientists, analysts, and software engineers to design data models that support high-quality analytics and real-time insights.</li>
</ul>

<ul>
<li style="margin-left:0px;">Lead data infrastructure projects including management of data on cloud platforms (AWS/Azure), data lake/warehouse implementations, and data quality frameworks.</li>
</ul>

<ul>
<li style="margin-left:0px;">Ensure data governance, security, and compliance best practices are followed.</li>
</ul>

<ul>
<li style="margin-left:0px;">Monitor and optimize the performance of data systems, addressing any issues proactively.</li>
</ul>

<ul>
<li style="margin-left:0px;">Mentor junior data engineers and contribute to establishing best practices in data engineering standards, tooling, and development workflows.</li>
</ul>

<ul>
<li style="margin-left:0px;">Stay current with emerging technologies and trends in data engineering and recommend improvements as needed.</li>
</ul>

Requirements

<ul>
<li style="margin-left:0px;">Bachelor s or Master s degree in Computer Science, Engineering, or a related field.</li>
</ul>

<ul>
<li style="margin-left:0px;">8+ years of hands-on experience in data engineering or backend software development roles.</li>
</ul>

<ul>
<li style="margin-left:0px;">Proficiency with Python, SQL, and at least one data pipeline orchestration tool (e.g., Apache Airflow, Luigi, Prefect).</li>
</ul>

<ul>
<li style="margin-left:0px;">Strong experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Snowflake, Databricks).</li>
</ul>

<ul>
<li style="margin-left:0px;">Deep understanding of data modeling, data warehousing, and distributed systems.</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience with big data technologies such as Apache Spark, Kafka, Hadoop, etc.</li>
</ul>

<ul>
<li style="margin-left:0px;">Familiarity with DevOps practices (CI/CD, infrastructure as code, containerization with Docker/Kubernetes).</li>
</ul>

Preferred Qualifications

<ul>
<li style="margin-left:0px;">Experience working with real-time data processing and streaming data architectures.</li>
</ul>

<ul>
<li style="margin-left:0px;">Knowledge of data security and privacy regulations (e.g., GDPR, HIPAA).</li>
</ul>

<ul>
<li style="margin-left:0px;">Exposure to machine learning pipelines or supporting data science workflows.</li>
</ul>

<ul>
<li style="margin-left:0px;">Familiarity with prompt engineering and how LLM-based systems interact with data.</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience working in cross-functional teams and with stakeholders from non-technical domains. </li>
</ul>

Senior Data Engineer

Responsibilities Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., Spark, Databricks, Airflow, Snowflake, etc.). Develop ETL/ELT processes to ingest data from various structured and unstructured sources. Perform Exploratory Data Analysis (EDA) to uncover trends, validate data integrity, and derive insights that inform data product development and business decisions. Collaborate closely with data scientists, analysts, and software engineers to design data models that support high-quality analytics and real-time insights. Lead data infrastructure projects including management of data on cloud platforms (AWS/Azure), data lake/warehouse implementations, and data quality frameworks. Ensure data governance, security, and compliance best practices are followed. Monitor and optimize the performance of data systems, addressing any issues proactively. Mentor junior data engineers and contribute to establishing best practices in data engineering standards, tooling, and development workflows. Stay current with emerging technologies and trends in data engineering and recommend improvements as needed. Requirements Bachelor s or Master s degree in Computer Science, Engineering, or a related field. 8+ years of hands-on experience in data engineering or backend software development roles. Proficiency with Python, SQL, and at least one data pipeline orchestration tool (e.g., Apache Airflow, Luigi, Prefect). Strong experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Snowflake, Databricks). Deep understanding of data modeling, data warehousing, and distributed systems. Experience with big data technologies such as Apache Spark, Kafka, Hadoop, etc. Familiarity with DevOps practices (CI/CD, infrastructure as code, containerization with Docker/Kubernetes). Preferred Qualifications Experience working with real-time data processing and streaming data architectures. Knowledge of data security and privacy regulations (e.g., GDPR, HIPAA). Exposure to machine learning pipelines or supporting data science workflows. Familiarity with prompt engineering and how LLM-based systems interact with data. Experience working in cross-functional teams and with stakeholders from non-technical domains.

Senior Data Engineer in Delhi (UID-14024)

Job Description

Job Details

Skills Required for Senior Data Engineer

Job Description for Senior Data Engineer

Explore More Opportunities