Design, develop, and maintain data pipelines for ingestion, processing, and storage using SQL, Python, and Big Data technologies.
Build scalable solutions on Google BigQuery and manage large datasets efficiently.
Collaborate with Data Scientists, Analysts, and Business teams to understand requirements and deliver actionable data insights.
Optimize SQL queries, Python scripts, and BigQuery jobs for performance and cost efficiency.
Implement data governance, quality checks, and security standards across all data assets.
Monitor and troubleshoot ETL pipelines and data workflows to ensure reliability.
Participate in architecture discussions and recommend best practices for Big Data solutions.
Required Skills :
Strong experience in SQL, Python, and Big Data frameworks (Hadoop, Spark, or similar).
Hands-on experience with Google BigQuery and cloud-based data platforms.
Expertise in ETL / ELT processes and data warehousing concepts.
Experience with data modeling, data pipelines, and large-scale data processing.
Knowledge of cloud platforms (GCP, AWS, or Azure) is a plus.
Strong problem-solving, analytical, and communication skills.
Desired Skills :
Familiarity with Airflow, Dataflow, or other workflow orchestration tools.
Experience with BI tools like Tableau, Looker, or Power BI.
Certification in Google Cloud Data Engineering is a plus
(ref : hirist.tech)
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Lead Data Engineer • Bangalore
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