Requirements

<ul>
<li>dbt Expert knowledge of dbt Core/Cloud, including Jinja, Snapshots, and incremental models.</li>
</ul>

<ul>
<li>SQL Mastery of SQL (Snowflake, BigQuery, or Redshift dialects).</li>
</ul>

<ul>
<li>ETL/ELT Tools Experience with ingestion tools like Fivetran, Airbyte, or custom Python scripts.</li>
</ul>

<ul>
<li>Orchestration Familiarity with Airflow, Dagster, or Prefect for scheduling complex jobs.</li>
</ul>

<ul>
<li>Warehousing Hands-on experience with cloud data warehouses (Snowflake, BigQuery, or Databricks).</li>
</ul>

<ul>
<li>Software Skills Strong Git version control skills and familiarity with YAML configuration.</li>
</ul>

Key Responsibilities

<ul>
<li>Analytics Engineering: Design, develop, and maintain robust data transformation pipelines using dbt. Implement modularity, macros, and packages to streamline the modeling layer.</li>
</ul>

<ul>
<li>Data Modeling: Architect scalable data models using Star Schema or Data Vault 2.0 methodologies to ensure data is optimized for both storage and query performance.</li>
</ul>

<ul>
<li>Advanced SQL Development: Write, optimize, and tune complex SQL queries (Window functions, CTEs, Recursive queries) to extract insights from massive datasets.</li>
</ul>

<ul>
<li>ETL/ELT Workflow: Build and manage automated workflows that ingest data from various sources (APIs, SaaS tools, production DBs) into the cloud data warehouse.</li>
</ul>

<ul>
<li>Data Quality &amp; Testing: Implement automated testing within dbt to ensure data integrity, freshness, and accuracy. Maintain documentation using dbt docs.</li>
</ul>

<ul>
<li>CI/CD &amp; Version Control: Manage data codebases using Git, ensuring seamless deployments through automated CI/CD pipelines.</li>
</ul>

Data Engineer

India

Requirements dbt Expert knowledge of dbt Core/Cloud, including Jinja, Snapshots, and incremental models. SQL Mastery of SQL (Snowflake, BigQuery, or Redshift dialects). ETL/ELT Tools Experience with ingestion tools like Fivetran, Airbyte, or custom Python scripts. Orchestration Familiarity with Airflow, Dagster, or Prefect for scheduling complex jobs. Warehousing Hands-on experience with cloud data warehouses (Snowflake, BigQuery, or Databricks). Software Skills Strong Git version control skills and familiarity with YAML configuration. Key Responsibilities Analytics Engineering: Design, develop, and maintain robust data transformation pipelines using dbt. Implement modularity, macros, and packages to streamline the modeling layer. Data Modeling: Architect scalable data models using Star Schema or Data Vault 2.0 methodologies to ensure data is optimized for both storage and query performance. Advanced SQL Development: Write, optimize, and tune complex SQL queries (Window functions, CTEs, Recursive queries) to extract insights from massive datasets. ETL/ELT Workflow: Build and manage automated workflows that ingest data from various sources (APIs, SaaS tools, production DBs) into the cloud data warehouse. Data Quality &amp; Testing: Implement automated testing within dbt to ensure data integrity, freshness, and accuracy. Maintain documentation using dbt docs. CI/CD &amp; Version Control: Manage data codebases using Git, ensuring seamless deployments through automated CI/CD pipelines.

Data Engineer · Chennai

Job highlights

Skillset required

Job Description

Job Description for Data Engineer

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