Big Data Sales Jobs

I need an experienced Python engineer who works confidently with AWS Glue to build and manage a small suite of data-integration jobs for a Hyderabad-based project. The core of the work is to design and automate Glue ETL pipelines that pull data from our production databases, catalog it accurately, and transform it into analytics-ready tables. Here is what I expect from the engagement: • Develop, test, and deploy Glue ETL jobs in Python. • Populate and maintain the Glue Data Catalog so new tables are discoverable and properly version-tracked. • Implement efficient transformation logic that cleans, enriches, and partitions data for downstream reporting. • Optimise job performance and cost by selecting the right worker types, job parameters, and database connectio...

I need an experienced Python engineer who works confidently with AWS Glue to build and manage a small suite of data-integration jobs for a Hyderabad-based project. The core of the work is to design and automate Glue ETL pipelines that pull data from our production databases, catalog it accurately, and transform it into analytics-ready tables. Here is what I expect from the engagement: • Develop, test, and deploy Glue ETL jobs in Python. • Populate and maintain the Glue Data Catalog so new tables are discoverable and properly version-tracked. • Implement efficient transformation logic that cleans, enriches, and partitions data for downstream reporting. • Optimise job performance and cost by selecting the right worker types, job parameters, and database connectio...

I have a Hadoop cluster holding several large data sets, and I need a seasoned PySpark developer who also writes rock-solid SQL. The immediate aim is to connect to the cluster (YARN/HDFS with Hive metastore), develop or refine PySpark jobs, optimise the accompanying SQL, and make sure everything runs smoothly end-to-end. You’ll receive access to a staging namespace plus a sample of the data. Once the logic checks out we’ll promote the code to the full environment. Deliverables • A clean, well-commented PySpark notebook or .py job that executes successfully on the cluster • The corresponding SQL script or view definitions ready for Hive or spark-sql • A concise README detailing execution steps, parameters, and expected outputs Acceptance criteria &bul...

I need an experienced Python engineer who works confidently with AWS Glue to build and manage a small suite of data-integration jobs for a Hyderabad-based project. The core of the work is to design and automate Glue ETL pipelines that pull data from our production databases, catalog it accurately, and transform it into analytics-ready tables. Here is what I expect from the engagement: • Develop, test, and deploy Glue ETL jobs in Python. • Populate and maintain the Glue Data Catalog so new tables are discoverable and properly version-tracked. • Implement efficient transformation logic that cleans, enriches, and partitions data for downstream reporting. • Optimise job performance and cost by selecting the right worker types, job parameters, and database connectio...

We are a B2B software and IT services company targeting SMBs and are looking for a proven cold email / outbound automation specialist to build and deploy a scalable, largely autopilot outbound system. This is not an AI development project. We are specifically looking for a practitioner experienced in building high-volume cold email engines using tools like Instantly, Smartlead, Clay, Apollo, Make, etc. The system should automatically: • Source and enrich qualified SMB prospects (no manual scraping or static purchased lists) • Personalize outreach at scale using AI-assisted dynamic fields • Manage multi-domain, multi-inbox infrastructure with proper warm-up and deliverability • Run automated sequences with intelligent follow-ups • Parse replies, qualify interest,...

I’m looking for a data scientist based anywhere in Latin America to help me create reliable predictive models for a finance-focused project. You’ll start with large historical datasets stored in SQL and deliver models that accurately forecast key financial indicators. I work mainly with Python, so you’ll find Pandas, NumPy, Scikit-learn and, when deep learning is justified, TensorFlow already in place. If you prefer R for certain tasks, that’s perfectly fine as long as the final workflow remains reproducible. The end-user needs to consume insights through Power BI, so once the model is validated I’ll ask you to craft intuitive dashboards that highlight drivers, confidence ranges and any red-flag anomalies the model detects. Solid statistical grounding is esse...