ETL engineer to upload data from Moscow Exchange API
Budget: $15 – $25 USD
Greetings!
Stack:
- Python
- Apache Airflow
- Clickhouse (preferably) / Posgress (ok)
I am looking for a person that could load hourly data from an API to a database and create a template script to run some technical analysis indicators (MACD / RSI / SMA) on that data.
Algorithmically:
1. Connecting to MOEX API. There are libraries on GitHub available that allow doing this. Alternatively, you may refer to MOEX API docs that are in English. Anyways, I will be there to help you.
2. Loading data from MOEX API. We will need to extract hourly data from about 20 different tickers in the following format: DATETIME | Open | High | Low | Close | Volume.
DATETIME should be in "%Y-%m-%d %H:%S' format or UNIX TIME.
3. Saving to the database. As I stated in the section below, the preferred database is Clickhouse. However, any database can be considered as an alternative. The end goal is to have all the data from the previous step in the table named 'russian_stock_prices' that looks like this:
DATETIME | TICKER | OPEN | HIGH | LOW | CLOSE | VOLUME
4. Last but not least, technical indicators should be executed on the last 50 candles for each ticker and saved back to the table 'russian_stock_indicators', which looks like this:
DATETIME | TICKER | RSI | MACD | SMA
Infrastructure:
I have already a running cluster of Airflow and clickhouse. All tasks regarding configuration I will take on my behalf.
Expectations:
My expectations regarding the project's deadline and costs are flexible. I would prefer quality over anything else.
I will gladly answer any questions. Thanks!
Stack:
- Python
- Apache Airflow
- Clickhouse (preferably) / Posgress (ok)
I am looking for a person that could load hourly data from an API to a database and create a template script to run some technical analysis indicators (MACD / RSI / SMA) on that data.
Algorithmically:
1. Connecting to MOEX API. There are libraries on GitHub available that allow doing this. Alternatively, you may refer to MOEX API docs that are in English. Anyways, I will be there to help you.
2. Loading data from MOEX API. We will need to extract hourly data from about 20 different tickers in the following format: DATETIME | Open | High | Low | Close | Volume.
DATETIME should be in "%Y-%m-%d %H:%S' format or UNIX TIME.
3. Saving to the database. As I stated in the section below, the preferred database is Clickhouse. However, any database can be considered as an alternative. The end goal is to have all the data from the previous step in the table named 'russian_stock_prices' that looks like this:
DATETIME | TICKER | OPEN | HIGH | LOW | CLOSE | VOLUME
4. Last but not least, technical indicators should be executed on the last 50 candles for each ticker and saved back to the table 'russian_stock_indicators', which looks like this:
DATETIME | TICKER | RSI | MACD | SMA
Infrastructure:
I have already a running cluster of Airflow and clickhouse. All tasks regarding configuration I will take on my behalf.
Expectations:
My expectations regarding the project's deadline and costs are flexible. I would prefer quality over anything else.
I will gladly answer any questions. Thanks!